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Jul 18, 2026
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Staging#516
iamzoltan merged 7 commits into
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@iamzoltan iamzoltan commented Jul 17, 2026

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Notebook Processing Failure Context

tutorials/W1D1_Generalization/W1D1_Tutorial1.ipynb

2026-07-17T04:56:24.1689932Z �[1;32m   1023�[0m �[43m        �[49m�[43mendpoint�[49m�[38;5;241;43m=�[39;49m�[43mendpoint�[49m�[43m,�[49m
2026-07-17T04:56:24.1693205Z �[1;32m   1024�[0m �[43m        �[49m�[43metag_timeout�[49m�[38;5;241;43m=�[39;49m�[43metag_timeout�[49m�[43m,�[49m
2026-07-17T04:56:24.1693863Z �[1;32m   1025�[0m �[43m        �[49m�[43mheaders�[49m�[38;5;241;43m=�[39;49m�[43mhf_headers�[49m�[43m,�[49m
2026-07-17T04:56:24.1694466Z �[1;32m   1026�[0m �[43m        �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
2026-07-17T04:56:24.1695261Z �[1;32m   1027�[0m �[43m        �[49m�[43mtoken�[49m�[38;5;241;43m=�[39;49m�[43mtoken�[49m�[43m,�[49m
2026-07-17T04:56:24.1695792Z �[1;32m   1028�[0m �[43m        �[49m�[38;5;66;43;03m# Additional options�[39;49;00m
2026-07-17T04:56:24.1696394Z �[1;32m   1029�[0m �[43m        �[49m�[43mlocal_files_only�[49m�[38;5;241;43m=�[39;49m�[43mlocal_files_only�[49m�[43m,�[49m
2026-07-17T04:56:24.1697086Z �[1;32m   1030�[0m �[43m        �[49m�[43mforce_download�[49m�[38;5;241;43m=�[39;49m�[43mforce_download�[49m�[43m,�[49m
2026-07-17T04:56:24.1697573Z �[1;32m   1031�[0m �[43m    �[49m�[43m)�[49m
2026-07-17T04:56:24.1697749Z 
2026-07-17T04:56:24.1698794Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:1175�[0m, in �[0;36m_hf_hub_download_to_cache_dir�[0;34m(cache_dir, repo_id, filename, repo_type, revision, endpoint, etag_timeout, headers, proxies, token, local_files_only, force_download)�[0m
2026-07-17T04:56:24.1700110Z �[1;32m   1172�[0m �[38;5;66;03m# Local file doesn't exist or etag isn't a match => retrieve file from remote (or cache)�[39;00m
2026-07-17T04:56:24.1700683Z �[1;32m   1174�[0m �[38;5;28;01mwith�[39;00m WeakFileLock(lock_path):
2026-07-17T04:56:24.1701113Z �[0;32m-> 1175�[0m     �[43m_download_to_tmp_and_move�[49m�[43m(�[49m
2026-07-17T04:56:24.1702290Z �[1;32m   1176�[0m �[43m        �[49m�[43mincomplete_path�[49m�[38;5;241;43m=�[39;49m�[43mPath�[49m�[43m(�[49m�[43mblob_path�[49m�[43m �[49m�[38;5;241;43m+�[39;49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43m.incomplete�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m�[43m,�[49m
2026-07-17T04:56:24.1703378Z �[1;32m   1177�[0m �[43m        �[49m�[43mdestination_path�[49m�[38;5;241;43m=�[39;49m�[43mPath�[49m�[43m(�[49m�[43mblob_path�[49m�[43m)�[49m�[43m,�[49m
2026-07-17T04:56:24.1704131Z �[1;32m   1178�[0m �[43m        �[49m�[43murl_to_download�[49m�[38;5;241;43m=�[39;49m�[43murl_to_download�[49m�[43m,�[49m
2026-07-17T04:56:24.1704750Z �[1;32m   1179�[0m �[43m        �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
2026-07-17T04:56:24.1705558Z �[1;32m   1180�[0m �[43m        �[49m�[43mheaders�[49m�[38;5;241;43m=�[39;49m�[43mheaders�[49m�[43m,�[49m
2026-07-17T04:56:24.1706177Z �[1;32m   1181�[0m �[43m        �[49m�[43mexpected_size�[49m�[38;5;241;43m=�[39;49m�[43mexpected_size�[49m�[43m,�[49m
2026-07-17T04:56:24.1706798Z �[1;32m   1182�[0m �[43m        �[49m�[43mfilename�[49m�[38;5;241;43m=�[39;49m�[43mfilename�[49m�[43m,�[49m
2026-07-17T04:56:24.1707435Z �[1;32m   1183�[0m �[43m        �[49m�[43mforce_download�[49m�[38;5;241;43m=�[39;49m�[43mforce_download�[49m�[43m,�[49m
2026-07-17T04:56:24.1708035Z �[1;32m   1184�[0m �[43m        �[49m�[43metag�[49m�[38;5;241;43m=�[39;49m�[43metag�[49m�[43m,�[49m
2026-07-17T04:56:24.1708634Z �[1;32m   1185�[0m �[43m        �[49m�[43mxet_file_data�[49m�[38;5;241;43m=�[39;49m�[43mxet_file_data�[49m�[43m,�[49m
2026-07-17T04:56:24.1709101Z �[1;32m   1186�[0m �[43m    �[49m�[43m)�[49m
2026-07-17T04:56:24.1709659Z �[1;32m   1187�[0m     �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m os�[38;5;241m.�[39mpath�[38;5;241m.�[39mexists(pointer_path):
2026-07-17T04:56:24.1710446Z �[1;32m   1188�[0m         _create_symlink(blob_path, pointer_path, new_blob�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)
2026-07-17T04:56:24.1710814Z 
2026-07-17T04:56:24.1711841Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:1742�[0m, in �[0;36m_download_to_tmp_and_move�[0;34m(incomplete_path, destination_path, url_to_download, proxies, headers, expected_size, filename, force_download, etag, xet_file_data)�[0m
2026-07-17T04:56:24.1713432Z �[1;32m   1735�[0m         �[38;5;28;01mif�[39;00m xet_file_data �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m �[38;5;129;01mand�[39;00m �[38;5;129;01mnot�[39;00m constants�[38;5;241m.�[39mHF_HUB_DISABLE_XET:
2026-07-17T04:56:24.1714223Z �[1;32m   1736�[0m             logger�[38;5;241m.�[39mwarning(
2026-07-17T04:56:24.1715309Z �[1;32m   1737�[0m                 �[38;5;124m"�[39m�[38;5;124mXet Storage is enabled for this repo, but the �[39m�[38;5;124m'�[39m�[38;5;124mhf_xet�[39m�[38;5;124m'�[39m�[38;5;124m package is not installed. �[39m�[38;5;124m"�[39m
2026-07-17T04:56:24.1716245Z �[1;32m   1738�[0m                 �[38;5;124m"�[39m�[38;5;124mFalling back to regular HTTP download. �[39m�[38;5;124m"�[39m
2026-07-17T04:56:24.1717174Z �[1;32m   1739�[0m                 �[38;5;124m"�[39m�[38;5;124mFor better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`�[39m�[38;5;124m"�[39m
2026-07-17T04:56:24.1717849Z �[1;32m   1740�[0m             )
2026-07-17T04:56:24.1718189Z �[0;32m-> 1742�[0m         �[43mhttp_get�[49m�[43m(�[49m
2026-07-17T04:56:24.1718603Z �[1;32m   1743�[0m �[43m            �[49m�[43murl_to_download�[49m�[43m,�[49m
2026-07-17T04:56:24.1719004Z �[1;32m   1744�[0m �[43m            �[49m�[43mf�[49m�[43m,�[49m
2026-07-17T04:56:24.1719501Z �[1;32m   1745�[0m �[43m            �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
2026-07-17T04:56:24.1720119Z �[1;32m   1746�[0m �[43m            �[49m�[43mresume_size�[49m�[38;5;241;43m=�[39;49m�[43mresume_size�[49m�[43m,�[49m
2026-07-17T04:56:24.1720719Z �[1;32m   1747�[0m �[43m            �[49m�[43mheaders�[49m�[38;5;241;43m=�[39;49m�[43mheaders�[49m�[43m,�[49m
2026-07-17T04:56:24.1721418Z �[1;32m   1748�[0m �[43m            �[49m�[43mexpected_size�[49m�[38;5;241;43m=�[39;49m�[43mexpected_size�[49m�[43m,�[49m
2026-07-17T04:56:24.1721891Z �[1;32m   1749�[0m �[43m        �[49m�[43m)�[49m
2026-07-17T04:56:24.1722705Z �[1;32m   1751�[0m logger�[38;5;241m.�[39minfo(�[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mDownload complete. Moving file to �[39m�[38;5;132;01m{�[39;00mdestination_path�[38;5;132;01m}�[39;00m�[38;5;124m"�[39m)
2026-07-17T04:56:24.1723475Z �[1;32m   1752�[0m _chmod_and_move(incomplete_path, destination_path)
2026-07-17T04:56:24.1723719Z 
2026-07-17T04:56:24.1724589Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:455�[0m, in �[0;36mhttp_get�[0;34m(url, temp_file, proxies, resume_size, headers, expected_size, displayed_filename, _nb_retries, _tqdm_bar)�[0m
2026-07-17T04:56:24.1726199Z �[1;32m    448�[0m     displayed_filename �[38;5;241m=�[39m �[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124m(…)�[39m�[38;5;132;01m{�[39;00mdisplayed_filename[�[38;5;241m-�[39m�[38;5;241m40�[39m:]�[38;5;132;01m}�[39;00m�[38;5;124m"�[39m
2026-07-17T04:56:24.1726973Z �[1;32m    450�[0m consistency_error_message �[38;5;241m=�[39m (
2026-07-17T04:56:24.1727861Z �[1;32m    451�[0m     �[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mConsistency check failed: file should be of size �[39m�[38;5;132;01m{�[39;00mexpected_size�[38;5;132;01m}�[39;00m�[38;5;124m but has size�[39m�[38;5;124m"�[39m
2026-07-17T04:56:24.1729568Z �[1;32m    452�[0m     �[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124m �[39m�[38;5;130;01m{{�[39;00m�[38;5;124mactual_size�[39m�[38;5;130;01m}}�[39;00m�[38;5;124m (�[39m�[38;5;132;01m{�[39;00mdisplayed_filename�[38;5;132;01m}�[39;00m�[38;5;124m).�[39m�[38;5;130;01m\n�[39;00m�[38;5;124mThis is usually due to network issues while downloading the file.�[39m�[38;5;124m"�[39m
2026-07-17T04:56:24.1730766Z �[1;32m    453�[0m     �[38;5;124m"�[39m�[38;5;124m Please retry with `force_download=True`.�[39m�[38;5;124m"�[39m
2026-07-17T04:56:24.1731198Z �[1;32m    454�[0m )
2026-07-17T04:56:24.1731595Z �[0;32m--> 455�[0m progress_cm �[38;5;241m=�[39m �[43m_get_progress_bar_context�[49m�[43m(�[49m
2026-07-17T04:56:24.1732183Z �[1;32m    456�[0m �[43m    �[49m�[43mdesc�[49m�[38;5;241;43m=�[39;49m�[43mdisplayed_filename�[49m�[43m,�[49m
2026-07-17T04:56:24.1732988Z �[1;32m    457�[0m �[43m    �[49m�[43mlog_level�[49m�[38;5;241;43m=�[39;49m�[43mlogger�[49m�[38;5;241;43m.�[39;49m�[43mgetEffectiveLevel�[49m�[43m(�[49m�[43m)�[49m�[43m,�[49m
2026-07-17T04:56:24.1733719Z �[1;32m    458�[0m �[43m    �[49m�[43mtotal�[49m�[38;5;241;43m=�[39;49m�[43mtotal�[49m�[43m,�[49m
2026-07-17T04:56:24.1734288Z �[1;32m    459�[0m �[43m    �[49m�[43minitial�[49m�[38;5;241;43m=�[39;49m�[43mresume_size�[49m�[43m,�[49m
2026-07-17T04:56:24.1735220Z �[1;32m    460�[0m �[43m    �[49m�[43mname�[49m�[38;5;241;43m=�[39;49m�[38;5;124;43m"�[39;49m�[38;5;124;43mhuggingface_hub.http_get�[39;49m�[38;5;124;43m"�[39;49m�[43m,�[49m
2026-07-17T04:56:24.1735957Z �[1;32m    461�[0m �[43m    �[49m�[43m_tqdm_bar�[49m�[38;5;241;43m=�[39;49m�[43m_tqdm_bar�[49m�[43m,�[49m
2026-07-17T04:56:24.1736378Z �[1;32m    462�[0m �[43m�[49m�[43m)�[49m
2026-07-17T04:56:24.1736797Z �[1;32m    464�[0m �[38;5;28;01mwith�[39;00m progress_cm �[38;5;28;01mas�[39;00m progress:
2026-07-17T04:56:24.1737898Z �[1;32m    465�[0m     �[38;5;28;01mif�[39;00m hf_transfer �[38;5;129;01mand�[39;00m total �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m �[38;5;129;01mand�[39;00m total �[38;5;241m>�[39m �[38;5;241m5�[39m �[38;5;241m*�[39m constants�[38;5;241m.�[39mDOWNLOAD_CHUNK_SIZE:
2026-07-17T04:56:24.1738620Z 
2026-07-17T04:56:24.1739402Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/utils/tqdm.py:299�[0m, in �[0;36m_get_progress_bar_context�[0;34m(desc, log_level, total, initial, unit, unit_scale, name, _tqdm_bar)�[0m
2026-07-17T04:56:24.1740323Z �[1;32m    294�[0m     �[38;5;28;01mreturn�[39;00m nullcontext(_tqdm_bar)
2026-07-17T04:56:24.1740974Z �[1;32m    295�[0m     �[38;5;66;03m# ^ `contextlib.nullcontext` mimics a context manager that does nothing�[39;00m
2026-07-17T04:56:24.1741662Z �[1;32m    296�[0m     �[38;5;66;03m#   Makes it easier to use the same code path for both cases but in the later�[39;00m
2026-07-17T04:56:24.1742338Z �[1;32m    297�[0m     �[38;5;66;03m#   case, the progress bar is not closed when exiting the context manager.�[39;00m
2026-07-17T04:56:24.1742887Z �[0;32m--> 299�[0m �[38;5;28;01mreturn�[39;00m �[43mtqdm�[49m�[43m(�[49m
2026-07-17T04:56:24.1743367Z �[1;32m    300�[0m �[43m    �[49m�[43munit�[49m�[38;5;241;43m=�[39;49m�[43munit�[49m�[43m,�[49m
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2026-07-17T04:56:24.1746637Z �[1;32m    305�[0m �[43m    �[49m�[43mdisable�[49m�[38;5;241;43m=�[39;49m�[43mis_tqdm_disabled�[49m�[43m(�[49m�[43mlog_level�[49m�[38;5;241;43m=�[39;49m�[43mlog_level�[49m�[43m)�[49m�[43m,�[49m
2026-07-17T04:56:24.1747400Z �[1;32m    306�[0m �[43m    �[49m�[43mname�[49m�[38;5;241;43m=�[39;49m�[43mname�[49m�[43m,�[49m
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2026-07-17T04:56:24.1747982Z 
2026-07-17T04:56:24.1748579Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/utils/tqdm.py:225�[0m, in �[0;36mtqdm.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T04:56:24.1749473Z �[1;32m    223�[0m �[38;5;28;01mif�[39;00m are_progress_bars_disabled(name):
2026-07-17T04:56:24.1750088Z �[1;32m    224�[0m     kwargs[�[38;5;124m"�[39m�[38;5;124mdisable�[39m�[38;5;124m"�[39m] �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T04:56:24.1751145Z �[0;32m--> 225�[0m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[38;5;21;43m__init__�[39;49m�[43m(�[49m�[38;5;241;43m*�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m*�[39;49m�[38;5;241;43m*�[39;49m�[43mkwargs�[49m�[43m)�[49m
2026-07-17T04:56:24.1751756Z 
2026-07-17T04:56:24.1752326Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T04:56:24.1753190Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T04:56:24.1753842Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T04:56:24.1754466Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T04:56:24.1755191Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T04:56:24.1755710Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T04:56:24.1756021Z 
2026-07-17T04:56:24.1756574Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T04:56:24.1757274Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T04:56:24.1757789Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T04:56:24.1758519Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T04:56:24.1759689Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T04:56:24.1760594Z 
2026-07-17T04:56:24.1760872Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T04:56:24.1761065Z 
2026-07-17T04:56:24.3571118Z ##[error]Process completed with exit code 1.

tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb

2026-07-17T04:56:26.1319676Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:50.2684828Z tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb failed quality control.
2026-07-17T04:56:50.2685490Z An error occurred while executing the following cell:
2026-07-17T04:56:50.2685975Z ============================== Failure ==============================
2026-07-17T04:56:50.2686610Z ------------------
2026-07-17T04:56:50.2687092Z def perturb_inputs(model, inputs, perturbation_strength):
2026-07-17T04:56:50.2687715Z     device = inputs.device
2026-07-17T04:56:50.2688603Z     # Perturb the inputs by adding random noise scaled by the perturbation strength and input strength
2026-07-17T04:56:50.2689734Z     input_strength = torch.norm(inputs, p=2, dim=-1, keepdim=True)  # Calculate the L2 norm of inputs
2026-07-17T04:56:50.2691296Z     noise = torch.rand(inputs.shape[0], 1, inputs.shape[2], device=device) * perturbation_strength * input_strength
2026-07-17T04:56:50.2692168Z     perturbed_inputs = inputs + noise
2026-07-17T04:56:50.2692741Z     return perturbed_inputs
2026-07-17T04:56:50.2693104Z 
2026-07-17T04:56:50.2695576Z def compute_loss(model, inputs, targets, criterion, device):
2026-07-17T04:56:50.2696221Z     batch_size = inputs.size(0)
2026-07-17T04:56:50.2696783Z     h = model.init_hidden(batch_size).to(device)  # Initialize hidden state
2026-07-17T04:56:50.2697390Z     losses = []
2026-07-17T04:56:50.2697801Z     for t in range(inputs.shape[1]):  # Iterate over time steps
2026-07-17T04:56:50.2698369Z         model_output = model(inputs[:, t, :], h)
2026-07-17T04:56:50.2698832Z         output, h, *rest = model_output[:2]
2026-07-17T04:56:50.2699533Z         loss = criterion(output, targets[:, t])  # Assume targets is a sequence of same length as inputs
2026-07-17T04:56:50.2700236Z         losses.append(loss)
2026-07-17T04:56:50.2700664Z     mean_loss = torch.mean(torch.stack(losses)).item()
2026-07-17T04:56:50.2701142Z     return mean_loss
2026-07-17T04:56:50.2701346Z 
2026-07-17T04:56:50.2701812Z def test_perturbed_inputs(model, perturbation_strengths, test_loader, criterion, device, max_error):
2026-07-17T04:56:50.2702908Z     model.eval()  # Set the model to evaluation mode
2026-07-17T04:56:50.2703671Z     perturbation_results = []
2026-07-17T04:56:50.2703925Z 
2026-07-17T04:56:50.2704091Z     for strength in perturbation_strengths:
2026-07-17T04:56:50.2704784Z         all_errors = []  # Store all errors for each perturbation strength to compute mean and s.d.
2026-07-17T04:56:50.2705551Z         print(f"Testing perturbation strength {strength}")
2026-07-17T04:56:50.2706176Z         for iteration in tqdm(range(30)):  # Repeat the procedure 30 times
2026-07-17T04:56:50.2706808Z             batch_errors = []  # Store errors for each batch
2026-07-17T04:56:50.2707153Z 
2026-07-17T04:56:50.2707322Z             for inputs, targets in test_loader:
2026-07-17T04:56:50.2707843Z                 inputs, targets = inputs.to(device), targets.to(device)
2026-07-17T04:56:50.2708397Z                 # Compute error for original inputs
2026-07-17T04:56:50.2709019Z                 # original_loss = compute_loss(model, inputs, targets, criterion, device)
2026-07-17T04:56:50.2709678Z                 # Compute error for perturbed inputs
2026-07-17T04:56:50.2709990Z 
2026-07-17T04:56:50.2710244Z                 perturbed_inputs = perturb_inputs(model, inputs, strength)
2026-07-17T04:56:50.2711032Z                 perturbed_loss = compute_loss(model, perturbed_inputs, targets, criterion, device)
2026-07-17T04:56:50.2711567Z 
2026-07-17T04:56:50.2711723Z                 # Store the normalized error.
2026-07-17T04:56:50.2712198Z                 rel_error = perturbed_loss / max_error * 100
2026-07-17T04:56:50.2712676Z                 batch_errors.append(rel_error)
2026-07-17T04:56:50.2712973Z 
2026-07-17T04:56:50.2713119Z             all_errors.extend(batch_errors)
2026-07-17T04:56:50.2713605Z 
2026-07-17T04:56:50.2713756Z         mean_error = np.mean(all_errors)
2026-07-17T04:56:50.2714168Z         std_error = np.std(all_errors)
2026-07-17T04:56:50.2714650Z         perturbation_results.append((mean_error, std_error))
2026-07-17T04:56:50.2715277Z         print(f"Completed testing for perturbation strength {strength}.")
2026-07-17T04:56:50.2715748Z 
2026-07-17T04:56:50.2715896Z     return perturbation_results
2026-07-17T04:56:50.2716152Z 
2026-07-17T04:56:50.2716509Z # Calculate the maximum error for a null model, the error when the output is constant.
2026-07-17T04:56:50.2717423Z max_error = ((outputs - outputs.mean(axis=[0, 1], keepdims=True)) ** 2).mean()
2026-07-17T04:56:50.2717935Z 
2026-07-17T04:56:50.2718156Z perturbation_strengths = [0.0125, 0.025, 0.05, 0.1, 0.2]
2026-07-17T04:56:50.2719195Z results_unregularized = test_perturbed_inputs(unregularized_model, perturbation_strengths, test_loader, nn.MSELoss(), device, max_error)
2026-07-17T04:56:50.2720887Z results_regularized = test_perturbed_inputs(regularized_model, perturbation_strengths, test_loader, nn.MSELoss(), device, max_error)
2026-07-17T04:56:50.2721793Z ------------------
2026-07-17T04:56:50.2721980Z 
2026-07-17T04:56:50.2722106Z ----- stdout -----
2026-07-17T04:56:50.2722441Z Testing perturbation strength 0.0125
2026-07-17T04:56:50.2722820Z ------------------
2026-07-17T04:56:50.2723002Z 
2026-07-17T04:56:50.2723786Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:50.2724620Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-17T04:56:50.2725248Z Cell �[0;32mIn[44], line 57�[0m
2026-07-17T04:56:50.2726930Z �[1;32m     54�[0m max_error �[38;5;241m=�[39m ((outputs �[38;5;241m-�[39m outputs�[38;5;241m.�[39mmean(axis�[38;5;241m=�[39m[�[38;5;241m0�[39m, �[38;5;241m1�[39m], keepdims�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)) �[38;5;241m*�[39m�[38;5;241m*�[39m �[38;5;241m2�[39m)�[38;5;241m.�[39mmean()
2026-07-17T04:56:50.2729000Z �[1;32m     56�[0m perturbation_strengths �[38;5;241m=�[39m [�[38;5;241m0.0125�[39m, �[38;5;241m0.025�[39m, �[38;5;241m0.05�[39m, �[38;5;241m0.1�[39m, �[38;5;241m0.2�[39m]
2026-07-17T04:56:50.2731979Z �[0;32m---> 57�[0m results_unregularized �[38;5;241m=�[39m �[43mtest_perturbed_inputs�[49m�[43m(�[49m�[43munregularized_model�[49m�[43m,�[49m�[43m �[49m�[43mperturbation_strengths�[49m�[43m,�[49m�[43m �[49m�[43mtest_loader�[49m�[43m,�[49m�[43m �[49m�[43mnn�[49m�[38;5;241;43m.�[39;49m�[43mMSELoss�[49m�[43m(�[49m�[43m)�[49m�[43m,�[49m�[43m �[49m�[43mdevice�[49m�[43m,�[49m�[43m �[49m�[43mmax_error�[49m�[43m)�[49m
2026-07-17T04:56:50.2735646Z �[1;32m     58�[0m results_regularized �[38;5;241m=�[39m test_perturbed_inputs(regularized_model, perturbation_strengths, test_loader, nn�[38;5;241m.�[39mMSELoss(), device, max_error)
2026-07-17T04:56:50.2736666Z 
2026-07-17T04:56:50.2737487Z Cell �[0;32mIn[44], line 28�[0m, in �[0;36mtest_perturbed_inputs�[0;34m(model, perturbation_strengths, test_loader, criterion, device, max_error)�[0m
2026-07-17T04:56:50.2739013Z �[1;32m     26�[0m all_errors �[38;5;241m=�[39m []  �[38;5;66;03m# Store all errors for each perturbation strength to compute mean and s.d.�[39;00m
2026-07-17T04:56:50.2740686Z �[1;32m     27�[0m �[38;5;28mprint�[39m(�[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mTesting perturbation strength �[39m�[38;5;132;01m{�[39;00mstrength�[38;5;132;01m}�[39;00m�[38;5;124m"�[39m)
2026-07-17T04:56:50.2742736Z �[0;32m---> 28�[0m �[38;5;28;01mfor�[39;00m iteration �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[38;5;28;43mrange�[39;49m�[43m(�[49m�[38;5;241;43m30�[39;49m�[43m)�[49m�[43m)�[49m:  �[38;5;66;03m# Repeat the procedure 30 times�[39;00m
2026-07-17T04:56:50.2744544Z �[1;32m     29�[0m     batch_errors �[38;5;241m=�[39m []  �[38;5;66;03m# Store errors for each batch�[39;00m
2026-07-17T04:56:50.2745510Z �[1;32m     31�[0m     �[38;5;28;01mfor�[39;00m inputs, targets �[38;5;129;01min�[39;00m test_loader:
2026-07-17T04:56:50.2745998Z 
2026-07-17T04:56:50.2746997Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T04:56:50.2748487Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T04:56:50.2749630Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T04:56:50.2750741Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T04:56:50.2751604Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T04:56:50.2752456Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T04:56:50.2752985Z 
2026-07-17T04:56:50.2754515Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T04:56:50.2755763Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T04:56:50.2756605Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T04:56:50.2757832Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T04:56:50.2759868Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T04:56:50.2761083Z 
2026-07-17T04:56:50.2761327Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T04:56:50.2761635Z 
2026-07-17T04:56:50.4550561Z ##[error]Process completed with exit code 1.

tutorials/W1D2_ComparingTasks/W1D2_Tutorial1.ipynb

2026-07-17T04:56:34.4756439Z Executing tutorials/W1D2_ComparingTasks/W1D2_Tutorial1.ipynb
2026-07-17T04:56:35.7763449Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:41.4122174Z tutorials/W1D2_ComparingTasks/W1D2_Tutorial1.ipynb failed quality control.
2026-07-17T04:56:41.4122826Z An error occurred while executing the following cell:
2026-07-17T04:56:41.4123234Z ------------------
2026-07-17T04:56:41.4123554Z # @title Import dependencies
2026-07-17T04:56:41.4123768Z 
2026-07-17T04:56:41.4123902Z # Import standard library dependencies
2026-07-17T04:56:41.4124253Z import os
2026-07-17T04:56:41.4124486Z import time
2026-07-17T04:56:41.4124718Z import gc
2026-07-17T04:56:41.4124956Z import logging
2026-07-17T04:56:41.4125235Z from pathlib import Path
2026-07-17T04:56:41.4125530Z import zipfile
2026-07-17T04:56:41.4125778Z import random
2026-07-17T04:56:41.4126029Z import contextlib
2026-07-17T04:56:41.4126292Z import io
2026-07-17T04:56:41.4127067Z 
2026-07-17T04:56:41.4127226Z # Import third-party libraries
2026-07-17T04:56:41.4127718Z import numpy as np
2026-07-17T04:56:41.4128023Z import matplotlib.pyplot as plt
2026-07-17T04:56:41.4128361Z import torch
2026-07-17T04:56:41.4128624Z import torch.nn as nn
2026-07-17T04:56:41.4128915Z import torch.optim as optim
2026-07-17T04:56:41.4129241Z import torch.nn.functional as F
2026-07-17T04:56:41.4129554Z import torchvision
2026-07-17T04:56:41.4129855Z import torchvision.transforms as transforms
2026-07-17T04:56:41.4130247Z from tqdm.notebook import tqdm
2026-07-17T04:56:41.4130523Z from ipywidgets import Layout
2026-07-17T04:56:41.4130788Z from memory_profiler import profile
2026-07-17T04:56:41.4131044Z import requests
2026-07-17T04:56:41.4131277Z from sklearn.metrics import confusion_matrix
2026-07-17T04:56:41.4131579Z from torchmetrics import Accuracy
2026-07-17T04:56:41.4131869Z from torch.utils.data import DataLoader
2026-07-17T04:56:41.4132146Z import vibecheck
2026-07-17T04:56:41.4132349Z import torch
2026-07-17T04:56:41.4132544Z import torch.nn as nn
2026-07-17T04:56:41.4132774Z import torch.nn.functional as F
2026-07-17T04:56:41.4133101Z from torch.utils.data import DataLoader, SubsetRandomSampler
2026-07-17T04:56:41.4133495Z ============================== Failure ==============================
2026-07-17T04:56:41.4134128Z from pathlib import Path
2026-07-17T04:56:41.4134629Z import time
2026-07-17T04:56:41.4135059Z from tqdm import tqdm
2026-07-17T04:56:41.4135492Z ------------------
2026-07-17T04:56:41.4135788Z 
2026-07-17T04:56:41.4135963Z 
2026-07-17T04:56:41.4136481Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:41.4137752Z �[0;31mModuleNotFoundError�[0m                       Traceback (most recent call last)
2026-07-17T04:56:41.4138757Z Cell �[0;32mIn[3], line 25�[0m
2026-07-17T04:56:41.4139769Z �[1;32m     23�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01mtqdm�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mnotebook�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m tqdm
2026-07-17T04:56:41.4141527Z �[1;32m     24�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01mipywidgets�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m Layout
2026-07-17T04:56:41.4143093Z �[0;32m---> 25�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01mmemory_profiler�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m profile
2026-07-17T04:56:41.4144382Z �[1;32m     26�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mrequests�[39;00m
2026-07-17T04:56:41.4145812Z �[1;32m     27�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01msklearn�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mmetrics�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m confusion_matrix
2026-07-17T04:56:41.4146368Z 
2026-07-17T04:56:41.4146848Z �[0;31mModuleNotFoundError�[0m: No module named 'memory_profiler'
2026-07-17T04:56:41.4147328Z 
2026-07-17T04:56:41.6255909Z ##[error]Process completed with exit code 1.

tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb

2026-07-17T04:56:00.1441547Z Executing tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb
2026-07-17T04:56:01.4218149Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:12.0136174Z tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb failed quality control.
2026-07-17T04:56:12.0137391Z ============================== Failure ==============================
2026-07-17T04:56:12.0138170Z An error occurred while executing the following cell:
2026-07-17T04:56:12.0138792Z ------------------
2026-07-17T04:56:12.0139294Z # @title Extract model features with torchlens
2026-07-17T04:56:12.0139632Z 
2026-07-17T04:56:12.0139825Z return_layers = ['input_1', 'conv1', 'conv2', 'fc1', 'fc2']
2026-07-17T04:56:12.0141153Z features_model_imgs = extract_features(model, imgs, return_layers, plot = 'rolled') #comment this line if Graphviz installation was unsuccessful for you
2026-07-17T04:56:12.0142006Z 
2026-07-17T04:56:12.0142300Z features_model_advimgs = extract_features(model, adv_imgs, return_layers)
2026-07-17T04:56:12.0143035Z features_advmodel_imgs = extract_features(model_robust, imgs, return_layers)
2026-07-17T04:56:12.0143864Z features_advmodel_advimgs = extract_features(model_robust, adv_imgs_advmodel, return_layers)
2026-07-17T04:56:12.0144511Z ------------------
2026-07-17T04:56:12.0144684Z 
2026-07-17T04:56:12.0145023Z ----- stderr -----
2026-07-17T04:56:12.0146186Z /tmp/ipykernel_3551/794751295.py:348: DeprecationWarning: torchlens.log_forward_pass is deprecated; use torchlens.trace instead. The old paper-era name remains available as a compatibility shim.
2026-07-17T04:56:12.0147599Z   model_history = tl.log_forward_pass(model, imgs, layers_to_save='all', vis_opt=plot)
2026-07-17T04:56:12.0148191Z ------------------
2026-07-17T04:56:12.0148352Z 
2026-07-17T04:56:12.0148882Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:12.0149635Z �[0;31mTypeError�[0m                                 Traceback (most recent call last)
2026-07-17T04:56:12.0150209Z Cell �[0;32mIn[23], line 4�[0m
2026-07-17T04:56:12.0150772Z �[1;32m      1�[0m �[38;5;66;03m# @title Extract model features with torchlens�[39;00m
2026-07-17T04:56:12.0152337Z �[1;32m      3�[0m return_layers �[38;5;241m=�[39m [�[38;5;124m'�[39m�[38;5;124minput_1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mconv1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mconv2�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mfc1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mfc2�[39m�[38;5;124m'�[39m]
2026-07-17T04:56:12.0154702Z �[0;32m----> 4�[0m features_model_imgs �[38;5;241m=�[39m �[43mextract_features�[49m�[43m(�[49m�[43mmodel�[49m�[43m,�[49m�[43m �[49m�[43mimgs�[49m�[43m,�[49m�[43m �[49m�[43mreturn_layers�[49m�[43m,�[49m�[43m �[49m�[43mplot�[49m�[43m �[49m�[38;5;241;43m=�[39;49m�[43m �[49m�[38;5;124;43m'�[39;49m�[38;5;124;43mrolled�[39;49m�[38;5;124;43m'�[39;49m�[43m)�[49m �[38;5;66;03m#comment this line if Graphviz installation was unsuccessful for you�[39;00m
2026-07-17T04:56:12.0156817Z �[1;32m      6�[0m features_model_advimgs �[38;5;241m=�[39m extract_features(model, adv_imgs, return_layers)
2026-07-17T04:56:12.0157574Z �[1;32m      7�[0m features_advmodel_imgs �[38;5;241m=�[39m extract_features(model_robust, imgs, return_layers)
2026-07-17T04:56:12.0157950Z 
2026-07-17T04:56:12.0158297Z Cell �[0;32mIn[8], line 348�[0m, in �[0;36mextract_features�[0;34m(model, imgs, return_layers, plot)�[0m
2026-07-17T04:56:12.0159283Z �[1;32m    335�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mextract_features�[39m(model, imgs, return_layers, plot�[38;5;241m=�[39m�[38;5;124m'�[39m�[38;5;124mnone�[39m�[38;5;124m'�[39m):
2026-07-17T04:56:12.0160056Z �[1;32m    336�[0m �[38;5;250m    �[39m�[38;5;124;03m"""�[39;00m
2026-07-17T04:56:12.0160590Z �[1;32m    337�[0m �[38;5;124;03m    Extracts features from specified layers of the model.�[39;00m
2026-07-17T04:56:12.0161043Z �[1;32m    338�[0m 
2026-07-17T04:56:12.0161259Z �[0;32m   (...)�[0m
2026-07-17T04:56:12.0161849Z �[1;32m    346�[0m �[38;5;124;03m    - model_features (dict): A dictionary with layer names as keys and extracted features as values.�[39;00m
2026-07-17T04:56:12.0162481Z �[1;32m    347�[0m �[38;5;124;03m    """�[39;00m
2026-07-17T04:56:12.0163939Z �[0;32m--> 348�[0m     model_history �[38;5;241m=�[39m �[43mtl�[49m�[38;5;241;43m.�[39;49m�[43mlog_forward_pass�[49m�[43m(�[49m�[43mmodel�[49m�[43m,�[49m�[43m �[49m�[43mimgs�[49m�[43m,�[49m�[43m �[49m�[43mlayers_to_save�[49m�[38;5;241;43m=�[39;49m�[38;5;124;43m'�[39;49m�[38;5;124;43mall�[39;49m�[38;5;124;43m'�[39;49m�[43m,�[49m�[43m �[49m�[43mvis_opt�[49m�[38;5;241;43m=�[39;49m�[43mplot�[49m�[43m)�[49m
2026-07-17T04:56:12.0165472Z �[1;32m    349�[0m     model_features �[38;5;241m=�[39m {}
2026-07-17T04:56:12.0166101Z �[1;32m    350�[0m     �[38;5;28;01mfor�[39;00m layer �[38;5;129;01min�[39;00m return_layers:
2026-07-17T04:56:12.0166415Z 
2026-07-17T04:56:12.0167115Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/torchlens/__init__.py:422�[0m, in �[0;36m_legacy_trace_alias.<locals>._shim�[0;34m(*args, **kwargs)�[0m
2026-07-17T04:56:12.0167967Z �[1;32m    420�[0m _warn_legacy_api_name(name, replacement)
2026-07-17T04:56:12.0168593Z �[1;32m    421�[0m �[38;5;28;01mif�[39;00m name �[38;5;241m==�[39m �[38;5;124m"�[39m�[38;5;124mlog_forward_pass�[39m�[38;5;124m"�[39m:
2026-07-17T04:56:12.0170184Z �[0;32m--> 422�[0m     �[38;5;28;01mreturn�[39;00m �[43m_resolve_top_level�[49m�[43m(�[49m�[38;5;124;43m"�[39;49m�[38;5;124;43m_trace�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m�[43m(�[49m�[38;5;241;43m*�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m*�[39;49m�[38;5;241;43m*�[39;49m�[43m_translate_legacy_trace_kwargs�[49m�[43m(�[49m�[43mkwargs�[49m�[43m)�[49m�[43m)�[49m
2026-07-17T04:56:12.0171671Z �[1;32m    423�[0m �[38;5;28;01mif�[39;00m name �[38;5;241m==�[39m �[38;5;124m"�[39m�[38;5;124mvalidate_model_activations�[39m�[38;5;124m"�[39m:
2026-07-17T04:56:12.0172620Z �[1;32m    424�[0m     kwargs�[38;5;241m.�[39msetdefault(�[38;5;124m"�[39m�[38;5;124mscope�[39m�[38;5;124m"�[39m, �[38;5;124m"�[39m�[38;5;124mforward�[39m�[38;5;124m"�[39m)
2026-07-17T04:56:12.0173132Z 
2026-07-17T04:56:12.0173379Z �[0;31mTypeError�[0m: trace() got an unexpected keyword argument 'vis_opt'
2026-07-17T04:56:12.0173673Z 
2026-07-17T04:56:12.2920516Z ##[error]Process completed with exit code 1.

tutorials/W1D5_Microcircuits/W1D5_Tutorial1.ipynb

2026-07-17T04:56:06.2802185Z Executing tutorials/W1D5_Microcircuits/W1D5_Tutorial1.ipynb
2026-07-17T04:56:07.8993324Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:13.9538773Z 2026-07-17 04:56:13.921546: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /opt/hostedtoolcache/Python/3.10.20/x64/lib
2026-07-17T04:56:13.9540325Z 2026-07-17 04:56:13.921574: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2026-07-17T05:29:29.0456498Z ##[error]The operation was canceled.

tutorials/W1D5_Microcircuits/W1D5_Tutorial2.ipynb

Job not found for tutorials/W1D5_Microcircuits/W1D5_Tutorial2.ipynb

tutorials/W2D1_Macrocircuits/W2D1_Tutorial1.ipynb

2026-07-17T04:56:23.4295933Z Executing tutorials/W2D1_Macrocircuits/W2D1_Tutorial1.ipynb
2026-07-17T04:56:24.6294154Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:30.8874339Z tutorials/W2D1_Macrocircuits/W2D1_Tutorial1.ipynb failed quality control.
2026-07-17T04:56:30.8875025Z ============================== Failure ==============================
2026-07-17T04:56:30.8875437Z An error occurred while executing the following cell:
2026-07-17T04:56:30.8875764Z ------------------
2026-07-17T04:56:30.8876018Z #to_remove solution
2026-07-17T04:56:30.8876159Z 
2026-07-17T04:56:30.8876249Z set_seed(42)
2026-07-17T04:56:30.8876369Z 
2026-07-17T04:56:30.8876535Z def train_model(net, X, y, n_epochs, lr, progressbar=True):
2026-07-17T04:56:30.8876860Z     """
2026-07-17T04:56:30.8877063Z     Perform training of the network.
2026-07-17T04:56:30.8877232Z 
2026-07-17T04:56:30.8877314Z     Inputs:
2026-07-17T04:56:30.8877864Z     - net (nn.Sequential): network.
2026-07-17T04:56:30.8878140Z     - X (torch.tensor): input data.
2026-07-17T04:56:30.8878405Z     - y (torch.tensor): output data.
2026-07-17T04:56:30.8878728Z     - n_epochs (int): number of epochs to train the model for.
2026-07-17T04:56:30.8879131Z     - lr (float): learning rate for optimizer (we will use `Adam` by default).
2026-07-17T04:56:30.8879648Z     - progressbar (bool, default = True): whether to use additional bar for displaying training progress.
2026-07-17T04:56:30.8879984Z 
2026-07-17T04:56:30.8880075Z     Outputs:
2026-07-17T04:56:30.8880345Z     - Es (np.ndarray): array which contains loss for each epoch.
2026-07-17T04:56:30.8880964Z     """
2026-07-17T04:56:30.8881068Z 
2026-07-17T04:56:30.8881153Z     # Set up optimizer
2026-07-17T04:56:30.8881370Z     loss_fn = nn.MSELoss()
2026-07-17T04:56:30.8881634Z     optimizer = torch.optim.Adam(net.parameters(), lr = lr)
2026-07-17T04:56:30.8881833Z 
2026-07-17T04:56:30.8881916Z     # Run training loop
2026-07-17T04:56:30.8882134Z     Es = np.zeros(n_epochs)
2026-07-17T04:56:30.8882418Z     for n in (tqdm(range(n_epochs)) if progressbar else range(n_epochs)):
2026-07-17T04:56:30.8882719Z         y_pred = net(X)
2026-07-17T04:56:30.8882930Z         loss = loss_fn(y_pred, y)
2026-07-17T04:56:30.8883192Z         optimizer.zero_grad()
2026-07-17T04:56:30.8883408Z         loss.backward()
2026-07-17T04:56:30.8883608Z         optimizer.step()
2026-07-17T04:56:30.8883819Z         Es[n] = float(loss.detach())
2026-07-17T04:56:30.8883967Z 
2026-07-17T04:56:30.8884050Z     return Es
2026-07-17T04:56:30.8884147Z 
2026-07-17T04:56:30.8884246Z Es = train_model(net, X, y, 10, 1e-3)
2026-07-17T04:56:30.8884616Z np.testing.assert_allclose(Es[0], 0.0, err_msg = "Expected value of loss is different!", atol = 1e-3)
2026-07-17T04:56:30.8884987Z ------------------
2026-07-17T04:56:30.8885096Z 
2026-07-17T04:56:30.8885099Z 
2026-07-17T04:56:30.8885516Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:30.8885960Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-17T04:56:30.8886429Z Cell �[0;32mIn[23], line 37�[0m
2026-07-17T04:56:30.8886820Z �[1;32m     33�[0m         Es[n] �[38;5;241m=�[39m �[38;5;28mfloat�[39m(loss�[38;5;241m.�[39mdetach())
2026-07-17T04:56:30.8887208Z �[1;32m     35�[0m     �[38;5;28;01mreturn�[39;00m Es
2026-07-17T04:56:30.8887990Z �[0;32m---> 37�[0m Es �[38;5;241m=�[39m �[43mtrain_model�[49m�[43m(�[49m�[43mnet�[49m�[43m,�[49m�[43m �[49m�[43mX�[49m�[43m,�[49m�[43m �[49m�[43my�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m10�[39;49m�[43m,�[49m�[43m �[49m�[38;5;241;43m1e-3�[39;49m�[43m)�[49m
2026-07-17T04:56:30.8889223Z �[1;32m     38�[0m np�[38;5;241m.�[39mtesting�[38;5;241m.�[39massert_allclose(Es[�[38;5;241m0�[39m], �[38;5;241m0.0�[39m, err_msg �[38;5;241m=�[39m �[38;5;124m"�[39m�[38;5;124mExpected value of loss is different!�[39m�[38;5;124m"�[39m, atol �[38;5;241m=�[39m �[38;5;241m1e-3�[39m)
2026-07-17T04:56:30.8889807Z 
2026-07-17T04:56:30.8890091Z Cell �[0;32mIn[23], line 27�[0m, in �[0;36mtrain_model�[0;34m(net, X, y, n_epochs, lr, progressbar)�[0m
2026-07-17T04:56:30.8890642Z �[1;32m     25�[0m �[38;5;66;03m# Run training loop�[39;00m
2026-07-17T04:56:30.8891039Z �[1;32m     26�[0m Es �[38;5;241m=�[39m np�[38;5;241m.�[39mzeros(n_epochs)
2026-07-17T04:56:30.8891940Z �[0;32m---> 27�[0m �[38;5;28;01mfor�[39;00m n �[38;5;129;01min�[39;00m (�[43mtqdm�[49m�[43m(�[49m�[38;5;28;43mrange�[39;49m�[43m(�[49m�[43mn_epochs�[49m�[43m)�[49m�[43m)�[49m �[38;5;28;01mif�[39;00m progressbar �[38;5;28;01melse�[39;00m �[38;5;28mrange�[39m(n_epochs)):
2026-07-17T04:56:30.8892635Z �[1;32m     28�[0m     y_pred �[38;5;241m=�[39m net(X)
2026-07-17T04:56:30.8892970Z �[1;32m     29�[0m     loss �[38;5;241m=�[39m loss_fn(y_pred, y)
2026-07-17T04:56:30.8893161Z 
2026-07-17T04:56:30.8893669Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T04:56:30.8894492Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T04:56:30.8895060Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T04:56:30.8895602Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T04:56:30.8896058Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T04:56:30.8896546Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T04:56:30.8896830Z 
2026-07-17T04:56:30.8897343Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T04:56:30.8897946Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T04:56:30.8898478Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T04:56:30.8899201Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T04:56:30.8900332Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T04:56:30.8901319Z 
2026-07-17T04:56:30.8901542Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T04:56:30.8901750Z 
2026-07-17T04:56:31.0433411Z ##[error]Process completed with exit code 1.

tutorials/W2D1_Macrocircuits/W2D1_Tutorial2.ipynb

2026-07-17T04:56:16.0512306Z Executing tutorials/W2D1_Macrocircuits/W2D1_Tutorial2.ipynb
2026-07-17T04:56:17.1318586Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:23.8913817Z tutorials/W2D1_Macrocircuits/W2D1_Tutorial2.ipynb failed quality control.
2026-07-17T04:56:23.8914266Z ============================== Failure ==============================
2026-07-17T04:56:23.8914666Z An error occurred while executing the following cell:
2026-07-17T04:56:23.8914991Z ------------------
2026-07-17T04:56:23.8915284Z set_seed(42)
2026-07-17T04:56:23.8915445Z 
2026-07-17T04:56:23.8915750Z n_hids = np.unique(np.round(np.logspace(0, 3, 10))).astype(int)
2026-07-17T04:56:23.8916082Z 
2026-07-17T04:56:23.8916204Z std_devs = np.linspace(0, 1.0, 3)
2026-07-17T04:56:23.8916390Z 
2026-07-17T04:56:23.8916715Z def plot_error(x_train, y_train, x_test, y_test, std_devs, n_hids, n_hidden = 10, n_reps = 100, reg = 0.0):
2026-07-17T04:56:23.8917668Z     """
2026-07-17T04:56:23.8918086Z     Plot mean test error for distinct values of noise added to train dataset.
2026-07-17T04:56:23.8918439Z 
2026-07-17T04:56:23.8918526Z     Inputs:
2026-07-17T04:56:23.8918798Z     - x_train (np.ndarray): train input data.
2026-07-17T04:56:23.8919315Z     - y_train (np.ndarray): train target data.
2026-07-17T04:56:23.8919683Z     - x_test (np.ndarray): test input data.
2026-07-17T04:56:23.8920027Z     - y_test (np.ndarray): test target data.
2026-07-17T04:56:23.8920487Z     - std_devs (np.ndarray): different standard deviation values for noise.
2026-07-17T04:56:23.8921018Z     - n_hids (np.ndarray): different values for hidden layer size.
2026-07-17T04:56:23.8921326Z     - n_hidden (int, default = 10): size of hidden layer.
2026-07-17T04:56:23.8921634Z     - n_reps (int, default = 100): number of resamples for data.
2026-07-17T04:56:23.8921946Z     - reg (float, default = 0): regularization constant.
2026-07-17T04:56:23.8922190Z     """
2026-07-17T04:56:23.8922363Z     with plt.xkcd():
2026-07-17T04:56:23.8922561Z         for sd in tqdm(std_devs):
2026-07-17T04:56:23.8922802Z             ###################################################################
2026-07-17T04:56:23.8923074Z             ## Fill out the following then remove
2026-07-17T04:56:23.8923526Z             raise NotImplementedError("Student exercise: complete calculation of mean test error for different noise values.")
2026-07-17T04:56:23.8923995Z             ###################################################################
2026-07-17T04:56:23.8924476Z             test_errs = [sweep_test(x_train, y_train + ..., x_test, y_test, n_hidden = n_hid, n_reps = n_reps, reg = reg * (1 + sd)) for n_hid in n_hids]
2026-07-17T04:56:23.8924997Z             plt.loglog(n_hids,test_errs,'o-',label="std={}".format(sd))
2026-07-17T04:56:23.8925224Z 
2026-07-17T04:56:23.8925307Z         plt.legend()
2026-07-17T04:56:23.8925510Z         plt.xlabel('Number of Hidden Units')
2026-07-17T04:56:23.8925752Z         plt.ylabel('Test Error')
2026-07-17T04:56:23.8925958Z         plt.show()
2026-07-17T04:56:23.8926066Z 
2026-07-17T04:56:23.8926196Z plot_error(x_train, y_train, x_test, y_test, std_devs, n_hids)
2026-07-17T04:56:23.8926471Z ------------------
2026-07-17T04:56:23.8926572Z 
2026-07-17T04:56:23.8926576Z 
2026-07-17T04:56:23.8927124Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:23.8927565Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-17T04:56:23.8927901Z Cell �[0;32mIn[30], line 36�[0m
2026-07-17T04:56:23.8928323Z �[1;32m     33�[0m         plt�[38;5;241m.�[39mylabel(�[38;5;124m'�[39m�[38;5;124mTest Error�[39m�[38;5;124m'�[39m)
2026-07-17T04:56:23.8928750Z �[1;32m     34�[0m         plt�[38;5;241m.�[39mshow()
2026-07-17T04:56:23.8929717Z �[0;32m---> 36�[0m �[43mplot_error�[49m�[43m(�[49m�[43mx_train�[49m�[43m,�[49m�[43m �[49m�[43my_train�[49m�[43m,�[49m�[43m �[49m�[43mx_test�[49m�[43m,�[49m�[43m �[49m�[43my_test�[49m�[43m,�[49m�[43m �[49m�[43mstd_devs�[49m�[43m,�[49m�[43m �[49m�[43mn_hids�[49m�[43m)�[49m
2026-07-17T04:56:23.8930274Z 
2026-07-17T04:56:23.8930640Z Cell �[0;32mIn[30], line 23�[0m, in �[0;36mplot_error�[0;34m(x_train, y_train, x_test, y_test, std_devs, n_hids, n_hidden, n_reps, reg)�[0m
2026-07-17T04:56:23.8931144Z �[1;32m      8�[0m �[38;5;250m�[39m�[38;5;124;03m"""�[39;00m
2026-07-17T04:56:23.8931635Z �[1;32m      9�[0m �[38;5;124;03mPlot mean test error for distinct values of noise added to train dataset.�[39;00m
2026-07-17T04:56:23.8932021Z �[1;32m     10�[0m 
2026-07-17T04:56:23.8932214Z �[0;32m   (...)�[0m
2026-07-17T04:56:23.8932549Z �[1;32m     20�[0m �[38;5;124;03m- reg (float, default = 0): regularization constant.�[39;00m
2026-07-17T04:56:23.8932906Z �[1;32m     21�[0m �[38;5;124;03m"""�[39;00m
2026-07-17T04:56:23.8933224Z �[1;32m     22�[0m �[38;5;28;01mwith�[39;00m plt�[38;5;241m.�[39mxkcd():
2026-07-17T04:56:23.8933819Z �[0;32m---> 23�[0m     �[38;5;28;01mfor�[39;00m sd �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mstd_devs�[49m�[43m)�[49m:
2026-07-17T04:56:23.8937128Z �[1;32m     24�[0m         �[38;5;66;03m###################################################################�[39;00m
2026-07-17T04:56:23.8938147Z �[1;32m     25�[0m         �[38;5;66;03m## Fill out the following then remove�[39;00m
2026-07-17T04:56:23.8940225Z �[1;32m     26�[0m         �[38;5;28;01mraise�[39;00m �[38;5;167;01mNotImplementedError�[39;00m(�[38;5;124m"�[39m�[38;5;124mStudent exercise: complete calculation of mean test error for different noise values.�[39m�[38;5;124m"�[39m)
2026-07-17T04:56:23.8942171Z �[1;32m     27�[0m         �[38;5;66;03m###################################################################�[39;00m
2026-07-17T04:56:23.8942694Z 
2026-07-17T04:56:23.8943923Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T04:56:23.8945663Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T04:56:23.8946937Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T04:56:23.8948161Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T04:56:23.8949168Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T04:56:23.8950178Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T04:56:23.8950786Z 
2026-07-17T04:56:23.8951862Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T04:56:23.8953256Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T04:56:23.8954266Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T04:56:23.8955726Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T04:56:23.8958063Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T04:56:23.8959811Z 
2026-07-17T04:56:23.8960090Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T04:56:23.8960459Z 
2026-07-17T04:56:24.0512829Z ##[error]Process completed with exit code 1.

tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb

2026-07-17T04:56:09.5506347Z Executing tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb
2026-07-17T04:56:10.5825322Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:29.8911197Z tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb failed quality control.
2026-07-17T04:56:29.8911962Z ============================== Failure ==============================
2026-07-17T04:56:29.8912697Z An error occurred while executing the following cell:
2026-07-17T04:56:29.8913176Z ------------------
2026-07-17T04:56:29.8913554Z modular_agent = Agent(arg, ModularActor)
2026-07-17T04:56:29.8914036Z modular_agent.load(Path('agents/modular'), 0)
2026-07-17T04:56:29.8914525Z modular_df = evaluation(modular_agent)
2026-07-17T04:56:29.8915228Z ------------------
2026-07-17T04:56:29.8915433Z 
2026-07-17T04:56:29.8915440Z 
2026-07-17T04:56:29.8916020Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:29.8917301Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-17T04:56:29.8917982Z Cell �[0;32mIn[38], line 3�[0m
2026-07-17T04:56:29.8918561Z �[1;32m      1�[0m modular_agent �[38;5;241m=�[39m Agent(arg, ModularActor)
2026-07-17T04:56:29.8919703Z �[1;32m      2�[0m modular_agent�[38;5;241m.�[39mload(Path(�[38;5;124m'�[39m�[38;5;124magents/modular�[39m�[38;5;124m'�[39m), �[38;5;241m0�[39m)
2026-07-17T04:56:29.8920945Z �[0;32m----> 3�[0m modular_df �[38;5;241m=�[39m �[43mevaluation�[49m�[43m(�[49m�[43mmodular_agent�[49m�[43m)�[49m
2026-07-17T04:56:29.8921551Z 
2026-07-17T04:56:29.8921955Z Cell �[0;32mIn[37], line 28�[0m, in �[0;36mevaluation�[0;34m(agent, gain_factor)�[0m
2026-07-17T04:56:29.8922915Z �[1;32m     25�[0m target_x �[38;5;241m=�[39m []; target_y �[38;5;241m=�[39m []; target_r �[38;5;241m=�[39m []
2026-07-17T04:56:29.8923812Z �[1;32m     26�[0m rewarded �[38;5;241m=�[39m []; state_input_ �[38;5;241m=�[39m []
2026-07-17T04:56:29.8925188Z �[0;32m---> 28�[0m �[38;5;28;01mfor�[39;00m target_position �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtarget_positions�[49m�[43m)�[49m:
2026-07-17T04:56:29.8927046Z �[1;32m     29�[0m     state �[38;5;241m=�[39m env�[38;5;241m.�[39mreset(target_position�[38;5;241m=�[39mtarget_position, gain�[38;5;241m=�[39marg�[38;5;241m.�[39mprocess_gain_default �[38;5;241m*�[39m gain_factor)
2026-07-17T04:56:29.8928531Z �[1;32m     30�[0m     agent�[38;5;241m.�[39mobs_step�[38;5;241m.�[39mreset(env�[38;5;241m.�[39mgain)
2026-07-17T04:56:29.8929057Z 
2026-07-17T04:56:29.8930085Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T04:56:29.8931561Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T04:56:29.8932629Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T04:56:29.8933915Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T04:56:29.8934713Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T04:56:29.8935786Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T04:56:29.8936306Z 
2026-07-17T04:56:29.8937284Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T04:56:29.8938471Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T04:56:29.8939287Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T04:56:29.8940509Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T04:56:29.8942780Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T04:56:29.8944115Z 
2026-07-17T04:56:29.8944374Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T04:56:29.8944690Z 
2026-07-17T04:56:30.0638261Z ##[error]Process completed with exit code 1.

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial1.ipynb

2026-07-17T04:56:23.2643030Z Executing tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial1.ipynb
2026-07-17T04:56:24.5511471Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:28.0080866Z tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial1.ipynb failed quality control.
2026-07-17T04:56:28.0081731Z ============================== Failure ==============================
2026-07-17T04:56:28.0082342Z An error occurred while executing the following cell:
2026-07-17T04:56:28.0082825Z ------------------
2026-07-17T04:56:28.0083245Z # @title Imports
2026-07-17T04:56:28.0083431Z 
2026-07-17T04:56:28.0083565Z #working with data
2026-07-17T04:56:28.0084133Z import numpy as np
2026-07-17T04:56:28.0084334Z 
2026-07-17T04:56:28.0084457Z #plotting
2026-07-17T04:56:28.0084807Z import matplotlib.pyplot as plt
2026-07-17T04:56:28.0085199Z import logging
2026-07-17T04:56:28.0085386Z 
2026-07-17T04:56:28.0085945Z #interactive display
2026-07-17T04:56:28.0086328Z import ipywidgets as widgets
2026-07-17T04:56:28.0086580Z 
2026-07-17T04:56:28.0086694Z #modeling
2026-07-17T04:56:28.0086970Z import sspspace
2026-07-17T04:56:28.0087292Z import nengo_spa as spa
2026-07-17T04:56:28.0087659Z from scipy.special import softmax
2026-07-17T04:56:28.0088060Z ------------------
2026-07-17T04:56:28.0088246Z 
2026-07-17T04:56:28.0088252Z 
2026-07-17T04:56:28.0088829Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:28.0089714Z �[0;31mModuleNotFoundError�[0m                       Traceback (most recent call last)
2026-07-17T04:56:28.0090393Z Cell �[0;32mIn[3], line 15�[0m
2026-07-17T04:56:28.0090903Z �[1;32m     13�[0m �[38;5;66;03m#modeling�[39;00m
2026-07-17T04:56:28.0091625Z �[1;32m     14�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01msspspace�[39;00m
2026-07-17T04:56:28.0092920Z �[0;32m---> 15�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mnengo_spa�[39;00m�[38;5;250m �[39m�[38;5;28;01mas�[39;00m�[38;5;250m �[39m�[38;5;21;01mspa�[39;00m
2026-07-17T04:56:28.0094794Z �[1;32m     16�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01mscipy�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mspecial�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m softmax
2026-07-17T04:56:28.0095633Z 
2026-07-17T04:56:28.0095951Z �[0;31mModuleNotFoundError�[0m: No module named 'nengo_spa'
2026-07-17T04:56:28.0096339Z 
2026-07-17T04:56:28.1830309Z ##[error]Process completed with exit code 1.

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial2.ipynb

2026-07-17T04:56:20.7032576Z Executing tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial2.ipynb
2026-07-17T04:56:21.9707730Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:25.9151301Z tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial2.ipynb failed quality control.
2026-07-17T04:56:25.9152198Z An error occurred while executing the following cell:
2026-07-17T04:56:25.9152697Z ------------------
2026-07-17T04:56:25.9153071Z # @title Imports
2026-07-17T04:56:25.9153266Z 
2026-07-17T04:56:25.9153408Z #working with data
2026-07-17T04:56:25.9153733Z import numpy as np
2026-07-17T04:56:25.9153926Z 
2026-07-17T04:56:25.9154055Z #plotting
2026-07-17T04:56:25.9154410Z import matplotlib.pyplot as plt
2026-07-17T04:56:25.9154811Z import logging
2026-07-17T04:56:25.9155014Z 
2026-07-17T04:56:25.9155155Z #interactive display
2026-07-17T04:56:25.9155786Z import ipywidgets as widgets
2026-07-17T04:56:25.9156450Z 
2026-07-17T04:56:25.9156587Z #modeling
2026-07-17T04:56:25.9156875Z import sspspace
2026-07-17T04:56:25.9157217Z from scipy.special import softmax
2026-07-17T04:56:25.9157649Z from sklearn.metrics import log_loss
2026-07-17T04:56:25.9158146Z ============================== Failure ==============================
2026-07-17T04:56:25.9158893Z from sklearn.neural_network import MLPRegressor
2026-07-17T04:56:25.9159237Z 
2026-07-17T04:56:25.9159380Z import nengo_spa as spa
2026-07-17T04:56:25.9159979Z from nengo_spa.algebras.hrr_algebra import HrrProperties, HrrAlgebra
2026-07-17T04:56:25.9160767Z from nengo_spa.vector_generation import VectorsWithProperties
2026-07-17T04:56:25.9161444Z def make_vocabulary(vector_length):
2026-07-17T04:56:25.9162533Z     vec_generator = VectorsWithProperties(vector_length, algebra=HrrAlgebra(), properties = [HrrProperties.UNITARY, HrrProperties.POSITIVE])
2026-07-17T04:56:25.9163777Z     vocab = spa.Vocabulary(vector_length, pointer_gen=vec_generator)
2026-07-17T04:56:25.9164405Z     return vocab
2026-07-17T04:56:25.9164787Z ------------------
2026-07-17T04:56:25.9165053Z 
2026-07-17T04:56:25.9165229Z 
2026-07-17T04:56:25.9166283Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:25.9167206Z �[0;31mModuleNotFoundError�[0m                       Traceback (most recent call last)
2026-07-17T04:56:25.9167906Z Cell �[0;32mIn[4], line 19�[0m
2026-07-17T04:56:25.9169046Z �[1;32m     16�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01msklearn�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mmetrics�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m log_loss
2026-07-17T04:56:25.9171136Z �[1;32m     17�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01msklearn�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mneural_network�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m MLPRegressor
2026-07-17T04:56:25.9172844Z �[0;32m---> 19�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mnengo_spa�[39;00m�[38;5;250m �[39m�[38;5;28;01mas�[39;00m�[38;5;250m �[39m�[38;5;21;01mspa�[39;00m
2026-07-17T04:56:25.9174862Z �[1;32m     20�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01mnengo_spa�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01malgebras�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mhrr_algebra�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m HrrProperties, HrrAlgebra
2026-07-17T04:56:25.9177369Z �[1;32m     21�[0m �[38;5;28;01mfrom�[39;00m�[38;5;250m �[39m�[38;5;21;01mnengo_spa�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mvector_generation�[39;00m�[38;5;250m �[39m�[38;5;28;01mimport�[39;00m VectorsWithProperties
2026-07-17T04:56:25.9178341Z 
2026-07-17T04:56:25.9178673Z �[0;31mModuleNotFoundError�[0m: No module named 'nengo_spa'
2026-07-17T04:56:25.9179061Z 
2026-07-17T04:56:26.0877889Z ##[error]Process completed with exit code 1.

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial3.ipynb

2026-07-17T04:56:15.9568599Z Executing tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial3.ipynb
2026-07-17T04:56:16.7604144Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:18.3369691Z tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial3.ipynb failed quality control.
2026-07-17T04:56:18.3370475Z An error occurred while executing the following cell:
2026-07-17T04:56:18.3370954Z ============================== Failure ==============================
2026-07-17T04:56:18.3371462Z ------------------
2026-07-17T04:56:18.3371775Z # @title Imports
2026-07-17T04:56:18.3371980Z 
2026-07-17T04:56:18.3372465Z import matplotlib.pyplot as plt
2026-07-17T04:56:18.3373000Z import numpy as np
2026-07-17T04:56:18.3373460Z import logging
2026-07-17T04:56:18.3373648Z 
2026-07-17T04:56:18.3373786Z %matplotlib inline
2026-07-17T04:56:18.3373990Z 
2026-07-17T04:56:18.3374113Z import nengo
2026-07-17T04:56:18.3376171Z import nengo_spa as spa
2026-07-17T04:56:18.3376795Z 
2026-07-17T04:56:18.3376934Z seed = 0
2026-07-17T04:56:18.3377181Z ------------------
2026-07-17T04:56:18.3377344Z 
2026-07-17T04:56:18.3377349Z 
2026-07-17T04:56:18.3378100Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:18.3379290Z �[0;31mModuleNotFoundError�[0m                       Traceback (most recent call last)
2026-07-17T04:56:18.3380823Z Cell �[0;32mIn[4], line 9�[0m
2026-07-17T04:56:18.3381395Z �[1;32m      5�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mlogging�[39;00m
2026-07-17T04:56:18.3382562Z �[1;32m      7�[0m get_ipython()�[38;5;241m.�[39mrun_line_magic(�[38;5;124m'�[39m�[38;5;124mmatplotlib�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124minline�[39m�[38;5;124m'�[39m)
2026-07-17T04:56:18.3383632Z �[0;32m----> 9�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mnengo�[39;00m
2026-07-17T04:56:18.3385098Z �[1;32m     10�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mnengo_spa�[39;00m�[38;5;250m �[39m�[38;5;28;01mas�[39;00m�[38;5;250m �[39m�[38;5;21;01mspa�[39;00m
2026-07-17T04:56:18.3386209Z �[1;32m     12�[0m seed �[38;5;241m=�[39m �[38;5;241m0�[39m
2026-07-17T04:56:18.3386500Z 
2026-07-17T04:56:18.3386737Z �[0;31mModuleNotFoundError�[0m: No module named 'nengo'
2026-07-17T04:56:18.3387045Z 
2026-07-17T04:56:18.5341814Z ##[error]Process completed with exit code 1.

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial4.ipynb

Job not found for tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial4.ipynb

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb

2026-07-17T04:56:14.1195946Z Executing tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb
2026-07-17T04:56:15.0779926Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T04:56:23.1009329Z tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb failed quality control.
2026-07-17T04:56:23.1010034Z ============================== Failure ==============================
2026-07-17T04:56:23.1010555Z An error occurred while executing the following cell:
2026-07-17T04:56:23.1010967Z ------------------
2026-07-17T04:56:23.1011291Z train_sizes = np.linspace(0.25, 0.9, 5)
2026-07-17T04:56:23.1011860Z bound_performance, bound_models = test_performance(bound_phis, ys_rastrigin, train_sizes)
2026-07-17T04:56:23.1012949Z bundle_performance, bundle_models = test_performance(bundle_phis, ys_rastrigin, train_sizes)
2026-07-17T04:56:23.1014307Z plot_performance(bound_performance, bundle_performance, train_sizes * bound_phis.shape[0], "Rastrigin function - RMSE")
2026-07-17T04:56:23.1015040Z plt.ylim((-1, 20))
2026-07-17T04:56:23.1015301Z ------------------
2026-07-17T04:56:23.1015459Z 
2026-07-17T04:56:23.1015464Z 
2026-07-17T04:56:23.1015980Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T04:56:23.1016666Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-17T04:56:23.1017177Z Cell �[0;32mIn[15], line 2�[0m
2026-07-17T04:56:23.1017820Z �[1;32m      1�[0m train_sizes �[38;5;241m=�[39m np�[38;5;241m.�[39mlinspace(�[38;5;241m0.25�[39m, �[38;5;241m0.9�[39m, �[38;5;241m5�[39m)
2026-07-17T04:56:23.1019128Z �[0;32m----> 2�[0m bound_performance, bound_models �[38;5;241m=�[39m �[43mtest_performance�[49m�[43m(�[49m�[43mbound_phis�[49m�[43m,�[49m�[43m �[49m�[43mys_rastrigin�[49m�[43m,�[49m�[43m �[49m�[43mtrain_sizes�[49m�[43m)�[49m
2026-07-17T04:56:23.1020398Z �[1;32m      3�[0m bundle_performance, bundle_models �[38;5;241m=�[39m test_performance(bundle_phis, ys_rastrigin, train_sizes)
2026-07-17T04:56:23.1021777Z �[1;32m      4�[0m plot_performance(bound_performance, bundle_performance, train_sizes �[38;5;241m*�[39m bound_phis�[38;5;241m.�[39mshape[�[38;5;241m0�[39m], �[38;5;124m"�[39m�[38;5;124mRastrigin function - RMSE�[39m�[38;5;124m"�[39m)
2026-07-17T04:56:23.1022880Z 
2026-07-17T04:56:23.1023202Z Cell �[0;32mIn[14], line 24�[0m, in �[0;36mtest_performance�[0;34m(xs, ys, train_sizes)�[0m
2026-07-17T04:56:23.1023732Z �[1;32m     21�[0m performance �[38;5;241m=�[39m []
2026-07-17T04:56:23.1024108Z �[1;32m     23�[0m models �[38;5;241m=�[39m []
2026-07-17T04:56:23.1024784Z �[0;32m---> 24�[0m �[38;5;28;01mfor�[39;00m train_size �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtrain_sizes�[49m�[43m)�[49m:
2026-07-17T04:56:23.1025918Z �[1;32m     25�[0m     X_train, X_test, y_train, y_test �[38;5;241m=�[39m train_test_split(xs, ys, random_state�[38;5;241m=�[39m�[38;5;241m1�[39m, train_size�[38;5;241m=�[39mtrain_size)
2026-07-17T04:56:23.1026947Z �[1;32m     26�[0m     regr �[38;5;241m=�[39m LinearRegression()�[38;5;241m.�[39mfit(X_train, y_train)
2026-07-17T04:56:23.1027278Z 
2026-07-17T04:56:23.1027919Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T04:56:23.1028880Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T04:56:23.1029575Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T04:56:23.1030252Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T04:56:23.1030773Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T04:56:23.1031323Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T04:56:23.1031671Z 
2026-07-17T04:56:23.1032551Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T04:56:23.1033325Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T04:56:23.1033869Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T04:56:23.1034651Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T04:56:23.1035939Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T04:56:23.1036703Z 
2026-07-17T04:56:23.1037007Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T04:56:23.1037214Z 
2026-07-17T04:56:23.3586168Z ##[error]Process completed with exit code 1.

tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

Job not found for tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

tutorials/W2D5_Mysteries/W2D5_Tutorial1.ipynb

Job not found for tutorials/W2D5_Mysteries/W2D5_Tutorial1.ipynb

tutorials/W2D5_Mysteries/W2D5_Tutorial3.ipynb

Job not found for tutorials/W2D5_Mysteries/W2D5_Tutorial3.ipynb

@github-actions

github-actions Bot commented Jul 17, 2026

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Follow-up PR Created

A follow-up PR has been created for the notebooks that failed to process:

Follow-up PR: #517
Branch: reprocess-pr516-20260717053051

The failed notebooks have been reverted to their main branch versions in this PR.
Once this PR is merged, the follow-up PR can be used to reprocess the failed notebooks independently.

@github-actions github-actions Bot mentioned this pull request Jul 17, 2026
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@github-actions

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Notebook Processing Failure Context

projects/project-notebooks/Macrocircuits.ipynb

2026-07-17T05:37:07.4083352Z Executing projects/project-notebooks/Macrocircuits.ipynb
2026-07-17T05:37:08.6785953Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T05:37:11.9268157Z projects/project-notebooks/Macrocircuits.ipynb failed quality control.
2026-07-17T05:37:11.9268592Z ============================== Failure ==============================
2026-07-17T05:37:11.9269007Z An error occurred while executing the following cell:
2026-07-17T05:37:11.9269354Z ------------------
2026-07-17T05:37:11.9269712Z #@title Installing Dependencies (Colab GPU case, uncomment if you want to use this one)
2026-07-17T05:37:11.9270038Z 
2026-07-17T05:37:11.9270316Z import distutils.util
2026-07-17T05:37:11.9270587Z import os
2026-07-17T05:37:11.9270819Z import subprocess
2026-07-17T05:37:11.9271247Z if subprocess.run('nvidia-smi').returncode:
2026-07-17T05:37:11.9271622Z   raise RuntimeError(
2026-07-17T05:37:11.9272351Z       'Cannot communicate with GPU. '
2026-07-17T05:37:11.9272736Z       'Make sure you are using a GPU Colab runtime. '
2026-07-17T05:37:11.9273164Z       'Go to the Runtime menu and select Choose runtime type.')
2026-07-17T05:37:11.9273502Z 
2026-07-17T05:37:11.9273723Z # Add an ICD config so that glvnd can pick up the Nvidia EGL driver.
2026-07-17T05:37:11.9274315Z # This is usually installed as part of an Nvidia driver package, but the Colab
2026-07-17T05:37:11.9274964Z # kernel doesn't install its driver via APT, and as a result the ICD is missing.
2026-07-17T05:37:11.9275808Z # (https://github.com/NVIDIA/libglvnd/blob/master/src/EGL/icd_enumeration.md)
2026-07-17T05:37:11.9276404Z NVIDIA_ICD_CONFIG_PATH = '/usr/share/glvnd/egl_vendor.d/10_nvidia.json'
2026-07-17T05:37:11.9276745Z if not os.path.exists(NVIDIA_ICD_CONFIG_PATH):
2026-07-17T05:37:11.9277020Z   with open(NVIDIA_ICD_CONFIG_PATH, 'w') as f:
2026-07-17T05:37:11.9277255Z     f.write("""{
2026-07-17T05:37:11.9277447Z     "file_format_version" : "1.0.0",
2026-07-17T05:37:11.9277665Z     "ICD" : {
2026-07-17T05:37:11.9277848Z         "library_path" : "libEGL_nvidia.so.0"
2026-07-17T05:37:11.9278069Z     }
2026-07-17T05:37:11.9278226Z }
2026-07-17T05:37:11.9278371Z """)
2026-07-17T05:37:11.9278460Z 
2026-07-17T05:37:11.9278544Z print('Installing dm_control...')
2026-07-17T05:37:11.9278790Z !pip install dm_control>=1.0.16 --quiet
2026-07-17T05:37:11.9278948Z 
2026-07-17T05:37:11.9279110Z # Configure dm_control to use the EGL rendering backend (requires GPU)
2026-07-17T05:37:11.9279428Z %env MUJOCO_GL=egl
2026-07-17T05:37:11.9279543Z 
2026-07-17T05:37:11.9279735Z !echo Installed dm_control $(pip show dm_control | grep -Po "(?<=Version: ).+")
2026-07-17T05:37:11.9280077Z !pip install dm-acme --quiet
2026-07-17T05:37:11.9280287Z !mkdir output_videos
2026-07-17T05:37:11.9280462Z ------------------
2026-07-17T05:37:11.9280563Z 
2026-07-17T05:37:11.9280567Z 
2026-07-17T05:37:11.9281182Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T05:37:11.9281891Z �[0;31mFileNotFoundError�[0m                         Traceback (most recent call last)
2026-07-17T05:37:11.9282313Z Cell �[0;32mIn[7], line 6�[0m
2026-07-17T05:37:11.9282652Z �[1;32m      4�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mos�[39;00m
2026-07-17T05:37:11.9283087Z �[1;32m      5�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01msubprocess�[39;00m
2026-07-17T05:37:11.9283859Z �[0;32m----> 6�[0m �[38;5;28;01mif�[39;00m �[43msubprocess�[49m�[38;5;241;43m.�[39;49m�[43mrun�[49m�[43m(�[49m�[38;5;124;43m'�[39;49m�[38;5;124;43mnvidia-smi�[39;49m�[38;5;124;43m'�[39;49m�[43m)�[49m�[38;5;241m.�[39mreturncode:
2026-07-17T05:37:11.9284565Z �[1;32m      7�[0m   �[38;5;28;01mraise�[39;00m �[38;5;167;01mRuntimeError�[39;00m(
2026-07-17T05:37:11.9285017Z �[1;32m      8�[0m       �[38;5;124m'�[39m�[38;5;124mCannot communicate with GPU. �[39m�[38;5;124m'�[39m
2026-07-17T05:37:11.9285556Z �[1;32m      9�[0m       �[38;5;124m'�[39m�[38;5;124mMake sure you are using a GPU Colab runtime. �[39m�[38;5;124m'�[39m
2026-07-17T05:37:11.9286157Z �[1;32m     10�[0m       �[38;5;124m'�[39m�[38;5;124mGo to the Runtime menu and select Choose runtime type.�[39m�[38;5;124m'�[39m)
2026-07-17T05:37:11.9286733Z �[1;32m     12�[0m �[38;5;66;03m# Add an ICD config so that glvnd can pick up the Nvidia EGL driver.�[39;00m
2026-07-17T05:37:11.9287306Z �[1;32m     13�[0m �[38;5;66;03m# This is usually installed as part of an Nvidia driver package, but the Colab�[39;00m
2026-07-17T05:37:11.9287915Z �[1;32m     14�[0m �[38;5;66;03m# kernel doesn't install its driver via APT, and as a result the ICD is missing.�[39;00m
2026-07-17T05:37:11.9288546Z �[1;32m     15�[0m �[38;5;66;03m# (https://github.com/NVIDIA/libglvnd/blob/master/src/EGL/icd_enumeration.md)�[39;00m
2026-07-17T05:37:11.9288852Z 
2026-07-17T05:37:11.9289361Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/subprocess.py:503�[0m, in �[0;36mrun�[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)�[0m
2026-07-17T05:37:11.9290215Z �[1;32m    500�[0m     kwargs[�[38;5;124m'�[39m�[38;5;124mstdout�[39m�[38;5;124m'�[39m] �[38;5;241m=�[39m PIPE
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2026-07-17T05:37:11.9291751Z �[0;32m--> 503�[0m �[38;5;28;01mwith�[39;00m �[43mPopen�[49m�[43m(�[49m�[38;5;241;43m*�[39;49m�[43mpopenargs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m*�[39;49m�[38;5;241;43m*�[39;49m�[43mkwargs�[49m�[43m)�[49m �[38;5;28;01mas�[39;00m process:
2026-07-17T05:37:11.9292493Z �[1;32m    504�[0m     �[38;5;28;01mtry�[39;00m:
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2026-07-17T05:37:11.9293387Z 
2026-07-17T05:37:11.9294522Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/subprocess.py:971�[0m, in �[0;36mPopen.__init__�[0;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, user, group, extra_groups, encoding, errors, text, umask, pipesize)�[0m
2026-07-17T05:37:11.9295703Z �[1;32m    967�[0m         �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtext_mode:
2026-07-17T05:37:11.9296326Z �[1;32m    968�[0m             �[38;5;28mself�[39m�[38;5;241m.�[39mstderr �[38;5;241m=�[39m io�[38;5;241m.�[39mTextIOWrapper(�[38;5;28mself�[39m�[38;5;241m.�[39mstderr,
2026-07-17T05:37:11.9296922Z �[1;32m    969�[0m                     encoding�[38;5;241m=�[39mencoding, errors�[38;5;241m=�[39merrors)
2026-07-17T05:37:11.9297780Z �[0;32m--> 971�[0m     �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43m_execute_child�[49m�[43m(�[49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[43mexecutable�[49m�[43m,�[49m�[43m �[49m�[43mpreexec_fn�[49m�[43m,�[49m�[43m �[49m�[43mclose_fds�[49m�[43m,�[49m
2026-07-17T05:37:11.9298646Z �[1;32m    972�[0m �[43m                        �[49m�[43mpass_fds�[49m�[43m,�[49m�[43m �[49m�[43mcwd�[49m�[43m,�[49m�[43m �[49m�[43menv�[49m�[43m,�[49m
2026-07-17T05:37:11.9299338Z �[1;32m    973�[0m �[43m                        �[49m�[43mstartupinfo�[49m�[43m,�[49m�[43m �[49m�[43mcreationflags�[49m�[43m,�[49m�[43m �[49m�[43mshell�[49m�[43m,�[49m
2026-07-17T05:37:11.9299952Z �[1;32m    974�[0m �[43m                        �[49m�[43mp2cread�[49m�[43m,�[49m�[43m �[49m�[43mp2cwrite�[49m�[43m,�[49m
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2026-07-17T05:37:11.9301103Z �[1;32m    976�[0m �[43m                        �[49m�[43merrread�[49m�[43m,�[49m�[43m �[49m�[43merrwrite�[49m�[43m,�[49m
2026-07-17T05:37:11.9301565Z �[1;32m    977�[0m �[43m                        �[49m�[43mrestore_signals�[49m�[43m,�[49m
2026-07-17T05:37:11.9302177Z �[1;32m    978�[0m �[43m                        �[49m�[43mgid�[49m�[43m,�[49m�[43m �[49m�[43mgids�[49m�[43m,�[49m�[43m �[49m�[43muid�[49m�[43m,�[49m�[43m �[49m�[43mumask�[49m�[43m,�[49m
2026-07-17T05:37:11.9302735Z �[1;32m    979�[0m �[43m                        �[49m�[43mstart_new_session�[49m�[43m)�[49m
2026-07-17T05:37:11.9303076Z �[1;32m    980�[0m �[38;5;28;01mexcept�[39;00m:
2026-07-17T05:37:11.9303426Z �[1;32m    981�[0m     �[38;5;66;03m# Cleanup if the child failed starting.�[39;00m
2026-07-17T05:37:11.9304225Z �[1;32m    982�[0m     �[38;5;28;01mfor�[39;00m f �[38;5;129;01min�[39;00m �[38;5;28mfilter�[39m(�[38;5;28;01mNone�[39;00m, (�[38;5;28mself�[39m�[38;5;241m.�[39mstdin, �[38;5;28mself�[39m�[38;5;241m.�[39mstdout, �[38;5;28mself�[39m�[38;5;241m.�[39mstderr)):
2026-07-17T05:37:11.9304742Z 
2026-07-17T05:37:11.9305873Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/subprocess.py:1863�[0m, in �[0;36mPopen._execute_child�[0;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, restore_signals, gid, gids, uid, umask, start_new_session)�[0m
2026-07-17T05:37:11.9306980Z �[1;32m   1861�[0m     �[38;5;28;01mif�[39;00m errno_num �[38;5;241m!=�[39m �[38;5;241m0�[39m:
2026-07-17T05:37:11.9307415Z �[1;32m   1862�[0m         err_msg �[38;5;241m=�[39m os�[38;5;241m.�[39mstrerror(errno_num)
2026-07-17T05:37:11.9307891Z �[0;32m-> 1863�[0m     �[38;5;28;01mraise�[39;00m child_exception_type(errno_num, err_msg, err_filename)
2026-07-17T05:37:11.9308341Z �[1;32m   1864�[0m �[38;5;28;01mraise�[39;00m child_exception_type(err_msg)
2026-07-17T05:37:11.9308647Z 
2026-07-17T05:37:11.9308876Z �[0;31mFileNotFoundError�[0m: [Errno 2] No such file or directory: 'nvidia-smi'
2026-07-17T05:37:11.9309121Z 
2026-07-17T05:37:12.1829059Z ##[error]Process completed with exit code 1.

tutorials/W1D1_Generalization/W1D1_Tutorial1.ipynb

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2026-07-17T05:36:46.2952061Z �[1;32m   1029�[0m �[43m        �[49m�[43mlocal_files_only�[49m�[38;5;241;43m=�[39;49m�[43mlocal_files_only�[49m�[43m,�[49m
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2026-07-17T05:36:46.2953468Z 
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2026-07-17T05:36:46.2955960Z �[1;32m   1172�[0m �[38;5;66;03m# Local file doesn't exist or etag isn't a match => retrieve file from remote (or cache)�[39;00m
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2026-07-17T05:36:46.2967060Z 
2026-07-17T05:36:46.2968166Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:1742�[0m, in �[0;36m_download_to_tmp_and_move�[0;34m(incomplete_path, destination_path, url_to_download, proxies, headers, expected_size, filename, force_download, etag, xet_file_data)�[0m
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2026-07-17T05:36:46.2970813Z �[1;32m   1736�[0m             logger�[38;5;241m.�[39mwarning(
2026-07-17T05:36:46.2971729Z �[1;32m   1737�[0m                 �[38;5;124m"�[39m�[38;5;124mXet Storage is enabled for this repo, but the �[39m�[38;5;124m'�[39m�[38;5;124mhf_xet�[39m�[38;5;124m'�[39m�[38;5;124m package is not installed. �[39m�[38;5;124m"�[39m
2026-07-17T05:36:46.2972718Z �[1;32m   1738�[0m                 �[38;5;124m"�[39m�[38;5;124mFalling back to regular HTTP download. �[39m�[38;5;124m"�[39m
2026-07-17T05:36:46.2973711Z �[1;32m   1739�[0m                 �[38;5;124m"�[39m�[38;5;124mFor better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`�[39m�[38;5;124m"�[39m
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2026-07-17T05:36:46.2980502Z �[1;32m   1752�[0m _chmod_and_move(incomplete_path, destination_path)
2026-07-17T05:36:46.2980865Z 
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2026-07-17T05:36:46.2996868Z 
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2026-07-17T05:36:46.3006887Z 
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2026-07-17T05:36:46.3011114Z 
2026-07-17T05:36:46.3011728Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
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2026-07-17T05:36:46.3015394Z 
2026-07-17T05:36:46.3015977Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
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2026-07-17T05:36:46.3020005Z 
2026-07-17T05:36:46.3020169Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T05:36:46.3020387Z 
2026-07-17T05:36:46.5156732Z ##[error]Process completed with exit code 1.

tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb

2026-07-17T05:35:53.6985380Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T05:36:14.8977360Z tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb failed quality control.
2026-07-17T05:36:14.8978297Z ============================== Failure ==============================
2026-07-17T05:36:14.8979696Z An error occurred while executing the following cell:
2026-07-17T05:36:14.8980264Z ------------------
2026-07-17T05:36:14.8981090Z def perturb_inputs(model, inputs, perturbation_strength):
2026-07-17T05:36:14.8982075Z     device = inputs.device
2026-07-17T05:36:14.8983104Z     # Perturb the inputs by adding random noise scaled by the perturbation strength and input strength
2026-07-17T05:36:14.8984414Z     input_strength = torch.norm(inputs, p=2, dim=-1, keepdim=True)  # Calculate the L2 norm of inputs
2026-07-17T05:36:14.8985987Z     noise = torch.rand(inputs.shape[0], 1, inputs.shape[2], device=device) * perturbation_strength * input_strength
2026-07-17T05:36:14.8986839Z     perturbed_inputs = inputs + noise
2026-07-17T05:36:14.8987389Z     return perturbed_inputs
2026-07-17T05:36:14.8987720Z 
2026-07-17T05:36:14.8988190Z def compute_loss(model, inputs, targets, criterion, device):
2026-07-17T05:36:14.8988674Z     batch_size = inputs.size(0)
2026-07-17T05:36:14.8989303Z     h = model.init_hidden(batch_size).to(device)  # Initialize hidden state
2026-07-17T05:36:14.8990264Z     losses = []
2026-07-17T05:36:14.8990712Z     for t in range(inputs.shape[1]):  # Iterate over time steps
2026-07-17T05:36:14.8991626Z         model_output = model(inputs[:, t, :], h)
2026-07-17T05:36:14.8992225Z         output, h, *rest = model_output[:2]
2026-07-17T05:36:14.8993079Z         loss = criterion(output, targets[:, t])  # Assume targets is a sequence of same length as inputs
2026-07-17T05:36:14.8993936Z         losses.append(loss)
2026-07-17T05:36:14.8994473Z     mean_loss = torch.mean(torch.stack(losses)).item()
2026-07-17T05:36:14.8995031Z     return mean_loss
2026-07-17T05:36:14.8995257Z 
2026-07-17T05:36:14.8995682Z def test_perturbed_inputs(model, perturbation_strengths, test_loader, criterion, device, max_error):
2026-07-17T05:36:14.8996238Z     model.eval()  # Set the model to evaluation mode
2026-07-17T05:36:14.8996571Z     perturbation_results = []
2026-07-17T05:36:14.8996742Z 
2026-07-17T05:36:14.8996851Z     for strength in perturbation_strengths:
2026-07-17T05:36:14.8997306Z         all_errors = []  # Store all errors for each perturbation strength to compute mean and s.d.
2026-07-17T05:36:14.8997790Z         print(f"Testing perturbation strength {strength}")
2026-07-17T05:36:14.8998200Z         for iteration in tqdm(range(30)):  # Repeat the procedure 30 times
2026-07-17T05:36:14.8998613Z             batch_errors = []  # Store errors for each batch
2026-07-17T05:36:14.8998831Z 
2026-07-17T05:36:14.8998978Z             for inputs, targets in test_loader:
2026-07-17T05:36:14.8999338Z                 inputs, targets = inputs.to(device), targets.to(device)
2026-07-17T05:36:14.8999702Z                 # Compute error for original inputs
2026-07-17T05:36:14.9000111Z                 # original_loss = compute_loss(model, inputs, targets, criterion, device)
2026-07-17T05:36:14.9000532Z                 # Compute error for perturbed inputs
2026-07-17T05:36:14.9000737Z 
2026-07-17T05:36:14.9000912Z                 perturbed_inputs = perturb_inputs(model, inputs, strength)
2026-07-17T05:36:14.9002013Z                 perturbed_loss = compute_loss(model, perturbed_inputs, targets, criterion, device)
2026-07-17T05:36:14.9002551Z 
2026-07-17T05:36:14.9002678Z                 # Store the normalized error.
2026-07-17T05:36:14.9003237Z                 rel_error = perturbed_loss / max_error * 100
2026-07-17T05:36:14.9003776Z                 batch_errors.append(rel_error)
2026-07-17T05:36:14.9003981Z 
2026-07-17T05:36:14.9004091Z             all_errors.extend(batch_errors)
2026-07-17T05:36:14.9004285Z 
2026-07-17T05:36:14.9004386Z         mean_error = np.mean(all_errors)
2026-07-17T05:36:14.9004666Z         std_error = np.std(all_errors)
2026-07-17T05:36:14.9004993Z         perturbation_results.append((mean_error, std_error))
2026-07-17T05:36:14.9005415Z         print(f"Completed testing for perturbation strength {strength}.")
2026-07-17T05:36:14.9005698Z 
2026-07-17T05:36:14.9005801Z     return perturbation_results
2026-07-17T05:36:14.9005969Z 
2026-07-17T05:36:14.9006202Z # Calculate the maximum error for a null model, the error when the output is constant.
2026-07-17T05:36:14.9006746Z max_error = ((outputs - outputs.mean(axis=[0, 1], keepdims=True)) ** 2).mean()
2026-07-17T05:36:14.9007047Z 
2026-07-17T05:36:14.9007189Z perturbation_strengths = [0.0125, 0.025, 0.05, 0.1, 0.2]
2026-07-17T05:36:14.9007837Z results_unregularized = test_perturbed_inputs(unregularized_model, perturbation_strengths, test_loader, nn.MSELoss(), device, max_error)
2026-07-17T05:36:14.9008929Z results_regularized = test_perturbed_inputs(regularized_model, perturbation_strengths, test_loader, nn.MSELoss(), device, max_error)
2026-07-17T05:36:14.9009520Z ------------------
2026-07-17T05:36:14.9009651Z 
2026-07-17T05:36:14.9009733Z ----- stdout -----
2026-07-17T05:36:14.9009961Z Testing perturbation strength 0.0125
2026-07-17T05:36:14.9010223Z ------------------
2026-07-17T05:36:14.9010338Z 
2026-07-17T05:36:14.9010802Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T05:36:14.9011762Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-17T05:36:14.9012194Z Cell �[0;32mIn[44], line 57�[0m
2026-07-17T05:36:14.9013279Z �[1;32m     54�[0m max_error �[38;5;241m=�[39m ((outputs �[38;5;241m-�[39m outputs�[38;5;241m.�[39mmean(axis�[38;5;241m=�[39m[�[38;5;241m0�[39m, �[38;5;241m1�[39m], keepdims�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)) �[38;5;241m*�[39m�[38;5;241m*�[39m �[38;5;241m2�[39m)�[38;5;241m.�[39mmean()
2026-07-17T05:36:14.9014649Z �[1;32m     56�[0m perturbation_strengths �[38;5;241m=�[39m [�[38;5;241m0.0125�[39m, �[38;5;241m0.025�[39m, �[38;5;241m0.05�[39m, �[38;5;241m0.1�[39m, �[38;5;241m0.2�[39m]
2026-07-17T05:36:14.9016501Z �[0;32m---> 57�[0m results_unregularized �[38;5;241m=�[39m �[43mtest_perturbed_inputs�[49m�[43m(�[49m�[43munregularized_model�[49m�[43m,�[49m�[43m �[49m�[43mperturbation_strengths�[49m�[43m,�[49m�[43m �[49m�[43mtest_loader�[49m�[43m,�[49m�[43m �[49m�[43mnn�[49m�[38;5;241;43m.�[39;49m�[43mMSELoss�[49m�[43m(�[49m�[43m)�[49m�[43m,�[49m�[43m �[49m�[43mdevice�[49m�[43m,�[49m�[43m �[49m�[43mmax_error�[49m�[43m)�[49m
2026-07-17T05:36:14.9018329Z �[1;32m     58�[0m results_regularized �[38;5;241m=�[39m test_perturbed_inputs(regularized_model, perturbation_strengths, test_loader, nn�[38;5;241m.�[39mMSELoss(), device, max_error)
2026-07-17T05:36:14.9018959Z 
2026-07-17T05:36:14.9019474Z Cell �[0;32mIn[44], line 28�[0m, in �[0;36mtest_perturbed_inputs�[0;34m(model, perturbation_strengths, test_loader, criterion, device, max_error)�[0m
2026-07-17T05:36:14.9020462Z �[1;32m     26�[0m all_errors �[38;5;241m=�[39m []  �[38;5;66;03m# Store all errors for each perturbation strength to compute mean and s.d.�[39;00m
2026-07-17T05:36:14.9021772Z �[1;32m     27�[0m �[38;5;28mprint�[39m(�[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mTesting perturbation strength �[39m�[38;5;132;01m{�[39;00mstrength�[38;5;132;01m}�[39;00m�[38;5;124m"�[39m)
2026-07-17T05:36:14.9023101Z �[0;32m---> 28�[0m �[38;5;28;01mfor�[39;00m iteration �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[38;5;28;43mrange�[39;49m�[43m(�[49m�[38;5;241;43m30�[39;49m�[43m)�[49m�[43m)�[49m:  �[38;5;66;03m# Repeat the procedure 30 times�[39;00m
2026-07-17T05:36:14.9024104Z �[1;32m     29�[0m     batch_errors �[38;5;241m=�[39m []  �[38;5;66;03m# Store errors for each batch�[39;00m
2026-07-17T05:36:14.9024747Z �[1;32m     31�[0m     �[38;5;28;01mfor�[39;00m inputs, targets �[38;5;129;01min�[39;00m test_loader:
2026-07-17T05:36:14.9025069Z 
2026-07-17T05:36:14.9025711Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T05:36:14.9026655Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T05:36:14.9027356Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T05:36:14.9028039Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T05:36:14.9028568Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T05:36:14.9029123Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T05:36:14.9029465Z 
2026-07-17T05:36:14.9030203Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T05:36:14.9030977Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T05:36:14.9031765Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T05:36:14.9032567Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T05:36:14.9033999Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T05:36:14.9034774Z 
2026-07-17T05:36:14.9034937Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T05:36:14.9035143Z 
2026-07-17T05:36:15.0835918Z ##[error]Process completed with exit code 1.

tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb

2026-07-17T05:35:49.5448359Z Executing tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb
2026-07-17T05:35:50.5467336Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T05:36:08.8281194Z tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb failed quality control.
2026-07-17T05:36:08.8282140Z ============================== Failure ==============================
2026-07-17T05:36:08.8282738Z An error occurred while executing the following cell:
2026-07-17T05:36:08.8283228Z ------------------
2026-07-17T05:36:08.8283908Z # @title Extract model features with torchlens
2026-07-17T05:36:08.8284235Z 
2026-07-17T05:36:08.8284463Z return_layers = ['input_1', 'conv1', 'conv2', 'fc1', 'fc2']
2026-07-17T05:36:08.8286034Z features_model_imgs = extract_features(model, imgs, return_layers, plot = 'rolled') #comment this line if Graphviz installation was unsuccessful for you
2026-07-17T05:36:08.8286927Z 
2026-07-17T05:36:08.8287252Z features_model_advimgs = extract_features(model, adv_imgs, return_layers)
2026-07-17T05:36:08.8288036Z features_advmodel_imgs = extract_features(model_robust, imgs, return_layers)
2026-07-17T05:36:08.8288919Z features_advmodel_advimgs = extract_features(model_robust, adv_imgs_advmodel, return_layers)
2026-07-17T05:36:08.8289851Z ------------------
2026-07-17T05:36:08.8290045Z 
2026-07-17T05:36:08.8290167Z ----- stderr -----
2026-07-17T05:36:08.8291335Z /tmp/ipykernel_3164/794751295.py:348: DeprecationWarning: torchlens.log_forward_pass is deprecated; use torchlens.trace instead. The old paper-era name remains available as a compatibility shim.
2026-07-17T05:36:08.8292824Z   model_history = tl.log_forward_pass(model, imgs, layers_to_save='all', vis_opt=plot)
2026-07-17T05:36:08.8293450Z ------------------
2026-07-17T05:36:08.8293909Z 
2026-07-17T05:36:08.8294499Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T05:36:08.8295332Z �[0;31mTypeError�[0m                                 Traceback (most recent call last)
2026-07-17T05:36:08.8295961Z Cell �[0;32mIn[23], line 4�[0m
2026-07-17T05:36:08.8296590Z �[1;32m      1�[0m �[38;5;66;03m# @title Extract model features with torchlens�[39;00m
2026-07-17T05:36:08.8298634Z �[1;32m      3�[0m return_layers �[38;5;241m=�[39m [�[38;5;124m'�[39m�[38;5;124minput_1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mconv1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mconv2�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mfc1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mfc2�[39m�[38;5;124m'�[39m]
2026-07-17T05:36:08.8302299Z �[0;32m----> 4�[0m features_model_imgs �[38;5;241m=�[39m �[43mextract_features�[49m�[43m(�[49m�[43mmodel�[49m�[43m,�[49m�[43m �[49m�[43mimgs�[49m�[43m,�[49m�[43m �[49m�[43mreturn_layers�[49m�[43m,�[49m�[43m �[49m�[43mplot�[49m�[43m �[49m�[38;5;241;43m=�[39;49m�[43m �[49m�[38;5;124;43m'�[39;49m�[38;5;124;43mrolled�[39;49m�[38;5;124;43m'�[39;49m�[43m)�[49m �[38;5;66;03m#comment this line if Graphviz installation was unsuccessful for you�[39;00m
2026-07-17T05:36:08.8305084Z �[1;32m      6�[0m features_model_advimgs �[38;5;241m=�[39m extract_features(model, adv_imgs, return_layers)
2026-07-17T05:36:08.8306180Z �[1;32m      7�[0m features_advmodel_imgs �[38;5;241m=�[39m extract_features(model_robust, imgs, return_layers)
2026-07-17T05:36:08.8306756Z 
2026-07-17T05:36:08.8307283Z Cell �[0;32mIn[8], line 348�[0m, in �[0;36mextract_features�[0;34m(model, imgs, return_layers, plot)�[0m
2026-07-17T05:36:08.8308775Z �[1;32m    335�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mextract_features�[39m(model, imgs, return_layers, plot�[38;5;241m=�[39m�[38;5;124m'�[39m�[38;5;124mnone�[39m�[38;5;124m'�[39m):
2026-07-17T05:36:08.8309938Z �[1;32m    336�[0m �[38;5;250m    �[39m�[38;5;124;03m"""�[39;00m
2026-07-17T05:36:08.8310745Z �[1;32m    337�[0m �[38;5;124;03m    Extracts features from specified layers of the model.�[39;00m
2026-07-17T05:36:08.8311406Z �[1;32m    338�[0m 
2026-07-17T05:36:08.8311740Z �[0;32m   (...)�[0m
2026-07-17T05:36:08.8312687Z �[1;32m    346�[0m �[38;5;124;03m    - model_features (dict): A dictionary with layer names as keys and extracted features as values.�[39;00m
2026-07-17T05:36:08.8313894Z �[1;32m    347�[0m �[38;5;124;03m    """�[39;00m
2026-07-17T05:36:08.8316205Z �[0;32m--> 348�[0m     model_history �[38;5;241m=�[39m �[43mtl�[49m�[38;5;241;43m.�[39;49m�[43mlog_forward_pass�[49m�[43m(�[49m�[43mmodel�[49m�[43m,�[49m�[43m �[49m�[43mimgs�[49m�[43m,�[49m�[43m �[49m�[43mlayers_to_save�[49m�[38;5;241;43m=�[39;49m�[38;5;124;43m'�[39;49m�[38;5;124;43mall�[39;49m�[38;5;124;43m'�[39;49m�[43m,�[49m�[43m �[49m�[43mvis_opt�[49m�[38;5;241;43m=�[39;49m�[43mplot�[49m�[43m)�[49m
2026-07-17T05:36:08.8318163Z �[1;32m    349�[0m     model_features �[38;5;241m=�[39m {}
2026-07-17T05:36:08.8319093Z �[1;32m    350�[0m     �[38;5;28;01mfor�[39;00m layer �[38;5;129;01min�[39;00m return_layers:
2026-07-17T05:36:08.8319560Z 
2026-07-17T05:36:08.8320629Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/torchlens/__init__.py:422�[0m, in �[0;36m_legacy_trace_alias.<locals>._shim�[0;34m(*args, **kwargs)�[0m
2026-07-17T05:36:08.8321888Z �[1;32m    420�[0m _warn_legacy_api_name(name, replacement)
2026-07-17T05:36:08.8322996Z �[1;32m    421�[0m �[38;5;28;01mif�[39;00m name �[38;5;241m==�[39m �[38;5;124m"�[39m�[38;5;124mlog_forward_pass�[39m�[38;5;124m"�[39m:
2026-07-17T05:36:08.8325600Z �[0;32m--> 422�[0m     �[38;5;28;01mreturn�[39;00m �[43m_resolve_top_level�[49m�[43m(�[49m�[38;5;124;43m"�[39;49m�[38;5;124;43m_trace�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m�[43m(�[49m�[38;5;241;43m*�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m*�[39;49m�[38;5;241;43m*�[39;49m�[43m_translate_legacy_trace_kwargs�[49m�[43m(�[49m�[43mkwargs�[49m�[43m)�[49m�[43m)�[49m
2026-07-17T05:36:08.8327839Z �[1;32m    423�[0m �[38;5;28;01mif�[39;00m name �[38;5;241m==�[39m �[38;5;124m"�[39m�[38;5;124mvalidate_model_activations�[39m�[38;5;124m"�[39m:
2026-07-17T05:36:08.8329346Z �[1;32m    424�[0m     kwargs�[38;5;241m.�[39msetdefault(�[38;5;124m"�[39m�[38;5;124mscope�[39m�[38;5;124m"�[39m, �[38;5;124m"�[39m�[38;5;124mforward�[39m�[38;5;124m"�[39m)
2026-07-17T05:36:08.8330162Z 
2026-07-17T05:36:08.8330554Z �[0;31mTypeError�[0m: trace() got an unexpected keyword argument 'vis_opt'
2026-07-17T05:36:08.8331016Z 
2026-07-17T05:36:09.0016207Z ##[error]Process completed with exit code 1.

tutorials/W2D1_Macrocircuits/W2D1_Tutorial1.ipynb

Job not found for tutorials/W2D1_Macrocircuits/W2D1_Tutorial1.ipynb

tutorials/W2D1_Macrocircuits/W2D1_Tutorial2.ipynb

Job not found for tutorials/W2D1_Macrocircuits/W2D1_Tutorial2.ipynb

tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb

2026-07-17T05:36:16.0043771Z Executing tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb
2026-07-17T05:36:17.2268354Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T05:36:42.2529206Z tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb failed quality control.
2026-07-17T05:36:42.2529976Z ============================== Failure ==============================
2026-07-17T05:36:42.2531158Z An error occurred while executing the following cell:
2026-07-17T05:36:42.2531740Z ------------------
2026-07-17T05:36:42.2532206Z modular_agent = Agent(arg, ModularActor)
2026-07-17T05:36:42.2532786Z modular_agent.load(Path('agents/modular'), 0)
2026-07-17T05:36:42.2533341Z modular_df = evaluation(modular_agent)
2026-07-17T05:36:42.2533839Z ------------------
2026-07-17T05:36:42.2534106Z 
2026-07-17T05:36:42.2535887Z 
2026-07-17T05:36:42.2536883Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T05:36:42.2538100Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-17T05:36:42.2538760Z Cell �[0;32mIn[38], line 3�[0m
2026-07-17T05:36:42.2539354Z �[1;32m      1�[0m modular_agent �[38;5;241m=�[39m Agent(arg, ModularActor)
2026-07-17T05:36:42.2540504Z �[1;32m      2�[0m modular_agent�[38;5;241m.�[39mload(Path(�[38;5;124m'�[39m�[38;5;124magents/modular�[39m�[38;5;124m'�[39m), �[38;5;241m0�[39m)
2026-07-17T05:36:42.2541786Z �[0;32m----> 3�[0m modular_df �[38;5;241m=�[39m �[43mevaluation�[49m�[43m(�[49m�[43mmodular_agent�[49m�[43m)�[49m
2026-07-17T05:36:42.2542378Z 
2026-07-17T05:36:42.2542776Z Cell �[0;32mIn[37], line 28�[0m, in �[0;36mevaluation�[0;34m(agent, gain_factor)�[0m
2026-07-17T05:36:42.2543719Z �[1;32m     25�[0m target_x �[38;5;241m=�[39m []; target_y �[38;5;241m=�[39m []; target_r �[38;5;241m=�[39m []
2026-07-17T05:36:42.2544586Z �[1;32m     26�[0m rewarded �[38;5;241m=�[39m []; state_input_ �[38;5;241m=�[39m []
2026-07-17T05:36:42.2545727Z �[0;32m---> 28�[0m �[38;5;28;01mfor�[39;00m target_position �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtarget_positions�[49m�[43m)�[49m:
2026-07-17T05:36:42.2547772Z �[1;32m     29�[0m     state �[38;5;241m=�[39m env�[38;5;241m.�[39mreset(target_position�[38;5;241m=�[39mtarget_position, gain�[38;5;241m=�[39marg�[38;5;241m.�[39mprocess_gain_default �[38;5;241m*�[39m gain_factor)
2026-07-17T05:36:42.2549308Z �[1;32m     30�[0m     agent�[38;5;241m.�[39mobs_step�[38;5;241m.�[39mreset(env�[38;5;241m.�[39mgain)
2026-07-17T05:36:42.2549794Z 
2026-07-17T05:36:42.2550804Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T05:36:42.2552241Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T05:36:42.2553316Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T05:36:42.2554325Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T05:36:42.2555116Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T05:36:42.2555951Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T05:36:42.2556469Z 
2026-07-17T05:36:42.2557584Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T05:36:42.2558814Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T05:36:42.2559667Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T05:36:42.2560840Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T05:36:42.2562919Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T05:36:42.2564183Z 
2026-07-17T05:36:42.2564656Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T05:36:42.2564966Z 
2026-07-17T05:36:42.5073680Z ##[error]Process completed with exit code 1.

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb

2026-07-17T05:35:58.8357498Z Executing tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb
2026-07-17T05:35:59.8509868Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-17T05:36:23.1481726Z tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb failed quality control.
2026-07-17T05:36:23.1482522Z ============================== Failure ==============================
2026-07-17T05:36:23.1483228Z An error occurred while executing the following cell:
2026-07-17T05:36:23.1483785Z ------------------
2026-07-17T05:36:23.1484261Z train_sizes = np.linspace(0.25, 0.9, 5)
2026-07-17T05:36:23.1485060Z bound_performance, bound_models = test_performance(bound_phis, ys_rastrigin, train_sizes)
2026-07-17T05:36:23.1486105Z bundle_performance, bundle_models = test_performance(bundle_phis, ys_rastrigin, train_sizes)
2026-07-17T05:36:23.1487794Z plot_performance(bound_performance, bundle_performance, train_sizes * bound_phis.shape[0], "Rastrigin function - RMSE")
2026-07-17T05:36:23.1488748Z plt.ylim((-1, 20))
2026-07-17T05:36:23.1489321Z ------------------
2026-07-17T05:36:23.1489604Z 
2026-07-17T05:36:23.1490001Z 
2026-07-17T05:36:23.1490799Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-17T05:36:23.1491774Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-17T05:36:23.1492412Z Cell �[0;32mIn[15], line 2�[0m
2026-07-17T05:36:23.1493297Z �[1;32m      1�[0m train_sizes �[38;5;241m=�[39m np�[38;5;241m.�[39mlinspace(�[38;5;241m0.25�[39m, �[38;5;241m0.9�[39m, �[38;5;241m5�[39m)
2026-07-17T05:36:23.1495096Z �[0;32m----> 2�[0m bound_performance, bound_models �[38;5;241m=�[39m �[43mtest_performance�[49m�[43m(�[49m�[43mbound_phis�[49m�[43m,�[49m�[43m �[49m�[43mys_rastrigin�[49m�[43m,�[49m�[43m �[49m�[43mtrain_sizes�[49m�[43m)�[49m
2026-07-17T05:36:23.1496844Z �[1;32m      3�[0m bundle_performance, bundle_models �[38;5;241m=�[39m test_performance(bundle_phis, ys_rastrigin, train_sizes)
2026-07-17T05:36:23.1498751Z �[1;32m      4�[0m plot_performance(bound_performance, bundle_performance, train_sizes �[38;5;241m*�[39m bound_phis�[38;5;241m.�[39mshape[�[38;5;241m0�[39m], �[38;5;124m"�[39m�[38;5;124mRastrigin function - RMSE�[39m�[38;5;124m"�[39m)
2026-07-17T05:36:23.1500349Z 
2026-07-17T05:36:23.1500785Z Cell �[0;32mIn[14], line 24�[0m, in �[0;36mtest_performance�[0;34m(xs, ys, train_sizes)�[0m
2026-07-17T05:36:23.1501520Z �[1;32m     21�[0m performance �[38;5;241m=�[39m []
2026-07-17T05:36:23.1502040Z �[1;32m     23�[0m models �[38;5;241m=�[39m []
2026-07-17T05:36:23.1502963Z �[0;32m---> 24�[0m �[38;5;28;01mfor�[39;00m train_size �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtrain_sizes�[49m�[43m)�[49m:
2026-07-17T05:36:23.1504502Z �[1;32m     25�[0m     X_train, X_test, y_train, y_test �[38;5;241m=�[39m train_test_split(xs, ys, random_state�[38;5;241m=�[39m�[38;5;241m1�[39m, train_size�[38;5;241m=�[39mtrain_size)
2026-07-17T05:36:23.1505827Z �[1;32m     26�[0m     regr �[38;5;241m=�[39m LinearRegression()�[38;5;241m.�[39mfit(X_train, y_train)
2026-07-17T05:36:23.1506340Z 
2026-07-17T05:36:23.1507320Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-17T05:36:23.1508806Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-17T05:36:23.1510050Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-17T05:36:23.1511104Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-17T05:36:23.1511906Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-17T05:36:23.1512763Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-17T05:36:23.1513294Z 
2026-07-17T05:36:23.1514227Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-17T05:36:23.1515416Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-17T05:36:23.1516269Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-17T05:36:23.1517491Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-17T05:36:23.1519863Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-17T05:36:23.1521083Z 
2026-07-17T05:36:23.1521546Z �[0;31mIndexError�[0m: list index out of range
2026-07-17T05:36:23.1521861Z 
2026-07-17T05:36:23.3036366Z ##[error]Process completed with exit code 1.

tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

Job not found for tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

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github-actions Bot commented Jul 17, 2026

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Follow-up PR Created

A follow-up PR has been created for the notebooks that failed to process:

Follow-up PR: #518
Branch: reprocess-pr516-20260717062844

The failed notebooks have been reverted to their main branch versions in this PR.
Once this PR is merged, the follow-up PR can be used to reprocess the failed notebooks independently.

@github-actions github-actions Bot mentioned this pull request Jul 17, 2026
Merged
iamzoltan
iamzoltan commented Jul 18, 2026
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lgtm!

@iamzoltan
iamzoltan merged commit a49781e into main Jul 18, 2026
iamzoltan added a commit that referenced this pull request Jul 18, 2026
@iamzoltan
Merge pull request #518 from neuromatch/reprocess-pr516-20260717062844
a889d02 
Reprocess: Failed notebooks from PR #516
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@iamzoltan @OleBialas @actions-user